Source Code for Module test_suite.system_tests.relax_disp

   1  ############################################################################### 
   2  #                                                                             # 
   3  # Copyright (C) 2006-2014 Edward d'Auvergne                                   # 
   4  # Copyright (C) 2009 Sebastien Morin                                          # 
   5  # Copyright (C) 2013-2014 Troels E. Linnet                                    # 
   6  #                                                                             # 
   7  # This file is part of the program relax (http://www.nmr-relax.com).          # 
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  23   
  24  # Python module imports. 
  25  from os import F_OK, access, getcwd, path, sep 
  26  from numpy import array, asarray, exp, median, inf, log, save, std, sum, zeros 
  27  from minfx.generic import generic_minimise 
  28  from random import gauss 
  29  import re, math 
  30  from sys import version_info 
  31  from tempfile import mkdtemp, NamedTemporaryFile 
  32   
  33   
  34  # relax module imports. 
  35  from auto_analyses import relax_disp 
  36  from auto_analyses.relax_disp_repeat_cpmg import DIC_KEY_FORMAT, Relax_disp_rep 
  37  from data_store import Relax_data_store; ds = Relax_data_store() 
  38  import dep_check 
  39  from lib.dispersion.variables import EXP_TYPE_CPMG_DQ, EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST, EXP_TYPE_R1RHO, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LIST_ANALYTIC_CPMG, MODEL_LIST_FULL, MODEL_LIST_NUMERIC_CPMG, MODEL_LM63, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_R1RHO_2SITE, MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_PARAMS, MODEL_R2EFF, MODEL_TP02, MODEL_TAP03 
  40  from lib.errors import RelaxError 
  41  from lib.io import extract_data, get_file_path, open_read_file 
  42  from lib.spectrum.nmrpipe import show_apod_extract, show_apod_rmsd, show_apod_rmsd_dir_to_files, show_apod_rmsd_to_file 
  43  from pipe_control.mol_res_spin import display_spin, generate_spin_string, return_spin, spin_loop 
  44  from pipe_control.minimise import assemble_scaling_matrix 
  45  from pipe_control.pipes import display 
  46  from specific_analyses.relax_disp.checks import check_missing_r1 
  47  from specific_analyses.relax_disp.estimate_r2eff import estimate_r2eff 
  48  from specific_analyses.relax_disp.data import average_intensity, check_intensity_errors, generate_r20_key, get_curve_type, has_exponential_exp_type, has_r1rho_exp_type, loop_exp_frq, loop_exp_frq_offset_point, loop_exp_frq_offset_point_time, loop_time, return_grace_file_name_ini, return_param_key_from_data, spin_ids_to_containers 
  49  from specific_analyses.relax_disp.data import INTERPOLATE_DISP, INTERPOLATE_OFFSET, X_AXIS_DISP, X_AXIS_W_EFF, X_AXIS_THETA, Y_AXIS_R2_R1RHO, Y_AXIS_R2_EFF 
  50  from specific_analyses.relax_disp.model import models_info, nesting_param 
  51  from specific_analyses.relax_disp.parameters import linear_constraints 
  52  from status import Status; status = Status() 
  53  from target_functions.relax_fit_wrapper import Relax_fit_opt 
  54  from test_suite.system_tests.base_classes import SystemTestCase 
  55   
  56   
  57 -class Relax_disp(SystemTestCase): 
  58      """Class for testing various aspects specific to relaxation dispersion curve-fitting.""" 
  59   
  60 -    def __init__(self, methodName='runTest'): 
  61          """Skip certain tests if the C modules are non-functional. 
  62   
  63          @keyword methodName:    The name of the test. 
  64          @type methodName:       str 
  65          """ 
  66   
  67          # Execute the base class method. 
  68          super(Relax_disp, self).__init__(methodName) 
  69   
  70          # Tests to skip. 
  71          blacklist = [ 
  72              'test_m61b_data_to_m61b' 
  73          ] 
  74          if methodName in blacklist: 
  75              status.skipped_tests.append([methodName, None, self._skip_type]) 
  76   
  77          # Missing module. 
  78          if not dep_check.C_module_exp_fn: 
  79              # The list of tests to skip. 
  80              to_skip = [ 
  81                  "test_bug_atul_srivastava", 
  82                  "test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp", 
  83                  "test_bug_9999_slow_r1rho_r2eff_error_with_mc", 
  84                  "test_estimate_r2eff_err", 
  85                  "test_estimate_r2eff_err_auto", 
  86                  "test_estimate_r2eff_err_methods", 
  87                  "test_finite_value", 
  88                  "test_exp_fit", 
  89                  "test_m61_exp_data_to_m61", 
  90                  "test_r1rho_kjaergaard_auto", 
  91                  "test_r1rho_kjaergaard_auto_check_graphs", 
  92                  "test_r1rho_kjaergaard_man", 
  93                  "test_r1rho_kjaergaard_missing_r1", 
  94                  "test_value_write_calc_rotating_frame_params_auto_analysis" 
  95              ] 
  96   
  97              # Store in the status object. 
  98              if methodName in to_skip: 
  99                  status.skipped_tests.append([methodName, 'Relax curve-fitting C module', self._skip_type]) 
 100   
 101          # If not scipy.optimize.leastsq. 
 102          if not dep_check.scipy_module: 
 103              # The list of tests to skip. 
 104              to_skip = [ 
 105                  "test_estimate_r2eff_err_methods" 
 106              ] 
 107   
 108              # Store in the status object. 
 109              if methodName in to_skip: 
 110                  status.skipped_tests.append([methodName, 'scipy.optimize.leastsq module', self._skip_type]) 
 111   
 112          # If not NMRPipe showApod program in PATH. 
 113          if not dep_check.showApod_software: 
 114              # The list of tests to skip. 
 115              to_skip = [ 
 116                  "test_show_apod_extract", 
 117                  "test_show_apod_rmsd", 
 118                  "test_show_apod_rmsd_to_file", 
 119                  "test_show_apod_rmsd_dir_to_files" 
 120              ] 
 121   
 122              # Store in the status object. 
 123              if methodName in to_skip: 
 124                  status.skipped_tests.append([methodName, 'NMRPipe showApod program', self._skip_type]) 
 125   
 126          # If not matplotlib module 
 127          if not dep_check.matplotlib_module: 
 128              # The list of tests to skip. 
 129              to_skip = [ 
 130                  "test_repeat_cpmg" 
 131              ] 
 132   
 133              # Store in the status object. 
 134              if methodName in to_skip: 
 135                  status.skipped_tests.append([methodName, 'matplotlib module', self._skip_type]) 
 136   
 137   
 138 -    def setUp(self): 
 139          """Set up for all the functional tests.""" 
 140   
 141          # Create the data pipe. 
 142          self.interpreter.pipe.create('relax_disp', 'relax_disp') 
 143   
 144          # Create a temporary directory for dumping files. 
 145          ds.tmpdir = mkdtemp() 
 146          self.tmpdir = ds.tmpdir 
 147   
 148   
 149 -    def setup_bug_22146_unpacking_r2a_r2b_cluster(self, folder=None, model_analyse=None, places = 7): 
 150          """Setup data for the catch of U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered full dispersion models. 
 151   
 152          @keyword folder:            The name of the folder for the test data. 
 153          @type folder:               str 
 154          @keyword model_analyse:     The name of the model which will be tested. 
 155          @type model_analyse:        str 
 156          """ 
 157   
 158          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 159   
 160          # Data. 
 161          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22146_unpacking_r2a_r2b_cluster'+sep+folder 
 162   
 163          ## Experiments 
 164          # Exp 1 
 165          sfrq_1 = 500.0*1E6 
 166          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
 167          time_T2_1 = 0.05 
 168          ncycs_1 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 50] 
 169          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 170          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 171          r2eff_errs_1 = [0.0] * len(ncycs_1) 
 172          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
 173   
 174          sfrq_2 = 600.0*1E6 
 175          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
 176          time_T2_2 = 0.06 
 177          ncycs_2 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 60] 
 178          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 179          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 180          r2eff_errs_2 = [0.0] * len(ncycs_2) 
 181          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
 182   
 183          sfrq_3 = 700.0*1E6 
 184          r20_key_3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_3) 
 185          time_T2_3 = 0.07 
 186          ncycs_3 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 50, 70] 
 187          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 188          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 189          r2eff_errs_3 = [0.0] * len(ncycs_3) 
 190          exp_3 = [sfrq_3, time_T2_3, ncycs_3, r2eff_errs_3] 
 191   
 192          # Collect all exps 
 193          exps = [exp_1, exp_2, exp_3] 
 194   
 195          R20 = [5.1, 5.2, 5.3, 10.1, 10.2, 10.3, 6.1, 6.2, 6.3, 11.1, 11.2, 11.3, 7.1, 7.2, 7.3, 12.1, 12.2, 12.3, 8.1, 8.2, 8.3, 13.1, 13.2, 13.3] 
 196          dw_arr = [1.0, 2.0, 3.0, 4.0] 
 197          pA_arr = [0.9] 
 198          kex_arr = [1000.] 
 199   
 200          spins = [ 
 201                  ['Ala', 1, 'N', {'r2a': {r20_key_1: R20[0], r20_key_2: R20[1], r20_key_3: R20[2]}, 'r2b': {r20_key_1: R20[3], r20_key_2: R20[4], r20_key_3: R20[5]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[0]}], 
 202                  ['Ala', 2, 'N', {'r2a': {r20_key_1: R20[6], r20_key_2: R20[7], r20_key_3: R20[8]}, 'r2b': {r20_key_1: R20[9], r20_key_2: R20[10], r20_key_3: R20[11]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[1]}], 
 203                  ['Ala', 3, 'N', {'r2a': {r20_key_1: R20[12], r20_key_2: R20[13], r20_key_3: R20[14]}, 'r2b': {r20_key_1: R20[15], r20_key_2: R20[16], r20_key_3: R20[17]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[2]}], 
 204                  ['Ala', 4, 'N', {'r2a': {r20_key_1: R20[18], r20_key_2: R20[19], r20_key_3: R20[20]}, 'r2b': {r20_key_1: R20[21], r20_key_2: R20[22], r20_key_3: R20[23]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[3]}], 
 205                  ] 
 206   
 207          # Create the data pipe. 
 208          pipe_name = 'base pipe' 
 209          pipe_type = 'relax_disp' 
 210          pipe_bundle = 'relax_disp' 
 211          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type, bundle = pipe_bundle) 
 212   
 213          # Generate the sequence. 
 214          for res_name, res_num, spin_name, params in spins: 
 215              self.interpreter.spin.create(res_name=res_name, res_num=res_num, spin_name=spin_name) 
 216   
 217          # Set isotope 
 218          self.interpreter.spin.isotope('15N', spin_id='@N') 
 219   
 220          # Now loop over the experiments, to set the variables in relax. 
 221          exp_ids = [] 
 222          for exp_i in exps: 
 223              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 224              exp_id = 'CPMG_%3.1f' % (sfrq/1E6) 
 225              exp_ids.append(exp_id) 
 226   
 227              ids = [] 
 228              for ncyc in ncycs: 
 229                  nu_cpmg = ncyc / time_T2 
 230                  cur_id = '%s_%.1f' % (exp_id, nu_cpmg) 
 231                  ids.append(cur_id) 
 232   
 233                  # Set the spectrometer frequency. 
 234                  self.interpreter.spectrometer.frequency(id=cur_id, frq=sfrq) 
 235   
 236                  # Set the experiment type. 
 237                  self.interpreter.relax_disp.exp_type(spectrum_id=cur_id, exp_type=EXP_TYPE_CPMG_SQ) 
 238   
 239                  # Set the relaxation dispersion CPMG constant time delay T (in s). 
 240                  self.interpreter.relax_disp.relax_time(spectrum_id=cur_id, time=time_T2) 
 241   
 242                  # Set the relaxation dispersion CPMG frequencies. 
 243                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=cur_id, cpmg_frq=nu_cpmg) 
 244   
 245          print("\n\nThe experiment IDs are %s." % cdp.spectrum_ids) 
 246   
 247          ### Now do fitting. 
 248          # Change pipe. 
 249   
 250          pipe_name_MODEL = "%s_%s"%(pipe_name, model_analyse) 
 251          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_MODEL, bundle_to = pipe_bundle) 
 252          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 253   
 254          # Now read data in. 
 255          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
 256              exp_id = exp_ids[mi] 
 257              exp_i = exps[mi] 
 258              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 259   
 260              # Then loop over the spins. 
 261              for res_name, res_num, spin_name, params in spins: 
 262                  cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 263   
 264                  # Define file name 
 265                  file_name = "%s%s.txt" % (exp_id, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
 266   
 267                  # Read in the R2eff file to put into spin structure. 
 268                  self.interpreter.relax_disp.r2eff_read_spin(id=exp_id, spin_id=cur_spin_id, file=file_name, dir=data_path, disp_point_col=1, data_col=2, error_col=3) 
 269   
 270          # Then select model. 
 271          self.interpreter.relax_disp.select_model(model=model_analyse) 
 272   
 273          # Then cluster 
 274          self.interpreter.relax_disp.cluster('model_cluster', ":1-100") 
 275   
 276          # Grid search 
 277          low_arr = R20 + dw_arr + pA_arr + kex_arr 
 278          self.interpreter.minimise.grid_search(lower=low_arr, upper=low_arr, inc=1, constraints=True, verbosity=1) 
 279   
 280          # Then loop over the defined spins and read the parameters. 
 281          for i in range(len(spins)): 
 282              res_name, res_num, spin_name, params = spins[i] 
 283              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 284              cur_spin = return_spin(cur_spin_id) 
 285   
 286              for mo_param in cur_spin.params: 
 287                  print(mo_param) 
 288                  # The R2 is a dictionary, depending on spectrometer frequency. 
 289                  if isinstance(getattr(cur_spin, mo_param), dict): 
 290                      for key, val in list(getattr(cur_spin, mo_param).items()): 
 291                          should_be = params[mo_param][key] 
 292                          print(cur_spin.model, res_name, cur_spin_id, mo_param, key, float(val), should_be) 
 293                          self.assertAlmostEqual(val, should_be) 
 294                  else: 
 295                      should_be = float(params[mo_param]) 
 296                      val = getattr(cur_spin, mo_param) 
 297                      print(cur_spin.model, res_name, cur_spin_id, mo_param, val, should_be) 
 298                      self.assertAlmostEqual(val, should_be) 
 299   
 300              # Test chi2. 
 301              # At this point the chi-squared value at the solution should be zero, as the relaxation data was created with the same parameter values. 
 302              self.assertAlmostEqual(cur_spin.chi2, 0.0, places = places) 
 303   
 304   
 305 -    def setup_r1rho_kjaergaard(self, cluster_ids=[], read_R1=True): 
 306          """Set up the data for the test_r1rho_kjaergaard_*() system tests.""" 
 307   
 308          # The path to the data files. 
 309          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 310   
 311          # Set pipe name, bundle and type. 
 312          ds.pipe_name = 'base pipe' 
 313          ds.pipe_bundle = 'relax_disp' 
 314          ds.pipe_type = 'relax_disp' 
 315   
 316          # Create the data pipe. 
 317          self.interpreter.pipe.create(pipe_name=ds.pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type) 
 318   
 319          # Read the spins. 
 320          self.interpreter.spectrum.read_spins(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 321   
 322          # Name the isotope for field strength scaling. 
 323          self.interpreter.spin.isotope(isotope='15N') 
 324   
 325          # Set number of experiments to be used. 
 326          NR_exp = 70 
 327   
 328          # Load the experiments settings file. 
 329          expfile = open(data_path+sep+'exp_parameters_sort.txt', 'r') 
 330          expfileslines = expfile.readlines()[:NR_exp] 
 331          expfile.close() 
 332   
 333          # In MHz 
 334          yOBS = 81.050 
 335          # In ppm 
 336          yCAR = 118.078 
 337          centerPPM_N15 = yCAR 
 338   
 339          ## Read the chemical shift data. 
 340          self.interpreter.chemical_shift.read(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 341   
 342          # The lock power to field, has been found in an calibration experiment. 
 343          spin_lock_field_strengths_Hz = {'35': 431.0, '39': 651.2, '41': 800.5, '43': 984.0, '46': 1341.11, '48': 1648.5} 
 344   
 345          # Apply spectra settings. 
 346          # Count settings 
 347          j = 0 
 348          for i in range(len(expfileslines)): 
 349              line = expfileslines[i] 
 350              if line[0] == "#": 
 351                  continue 
 352              else: 
 353                  # DIRN I deltadof2 dpwr2slock ncyc trim ss sfrq 
 354                  DIRN = line.split()[0] 
 355                  I = int(line.split()[1]) 
 356                  deltadof2 = line.split()[2] 
 357                  dpwr2slock = line.split()[3] 
 358                  ncyc = int(line.split()[4]) 
 359                  trim = float(line.split()[5]) 
 360                  ss = int(line.split()[6]) 
 361                  set_sfrq = float(line.split()[7]) 
 362                  apod_rmsd = float(line.split()[8]) 
 363                  spin_lock_field_strength = spin_lock_field_strengths_Hz[dpwr2slock] 
 364   
 365                  # Calculate spin_lock time 
 366                  time_sl = 2*ncyc*trim 
 367   
 368                  # Define file name for peak list. 
 369                  FNAME = "%s_%s_%s_%s_max_standard.ser"%(I, deltadof2, dpwr2slock, ncyc) 
 370                  sp_id = "%s_%s_%s_%s"%(I, deltadof2, dpwr2slock, ncyc) 
 371   
 372                  # Load the peak intensities. 
 373                  self.interpreter.spectrum.read_intensities(file=FNAME, dir=data_path+sep+'peak_lists', spectrum_id=sp_id, int_method='height') 
 374   
 375                  # Set the peak intensity errors, as defined as the baseplane RMSD. 
 376                  self.interpreter.spectrum.baseplane_rmsd(error=apod_rmsd, spectrum_id=sp_id) 
 377   
 378                  # Set the relaxation dispersion experiment type. 
 379                  self.interpreter.relax_disp.exp_type(spectrum_id=sp_id, exp_type='R1rho') 
 380   
 381                  # Set The spin-lock field strength, nu1, in Hz 
 382                  self.interpreter.relax_disp.spin_lock_field(spectrum_id=sp_id, field=spin_lock_field_strength) 
 383   
 384                  # Calculating the spin-lock offset in ppm, from offsets values provided in Hz. 
 385                  frq_N15_Hz = yOBS * 1E6 
 386                  offset_ppm_N15 = float(deltadof2) / frq_N15_Hz * 1E6 
 387                  omega_rf_ppm = centerPPM_N15 + offset_ppm_N15 
 388   
 389                  # Set The spin-lock offset, omega_rf, in ppm. 
 390                  self.interpreter.relax_disp.spin_lock_offset(spectrum_id=sp_id, offset=omega_rf_ppm) 
 391   
 392                  # Set the relaxation times (in s). 
 393                  self.interpreter.relax_disp.relax_time(spectrum_id=sp_id, time=time_sl) 
 394   
 395                  # Set the spectrometer frequency. 
 396                  self.interpreter.spectrometer.frequency(id=sp_id, frq=set_sfrq, units='MHz') 
 397   
 398                  # Add to counter 
 399                  j += 1 
 400   
 401   
 402          print("Testing the number of settings") 
 403          print("Number of settings iterations is: %s. Number of cdp.exp_type is: %s"%(i, len(cdp.exp_type))) 
 404          self.assertEqual(70, len(expfileslines)) 
 405          self.assertEqual(69, j) 
 406          self.assertEqual(69, len(cdp.exp_type)) 
 407   
 408          # Cluster spins 
 409          for curspin in cluster_ids: 
 410              print("Adding spin %s to cluster"%curspin) 
 411              self.interpreter.relax_disp.cluster('model_cluster', curspin) 
 412   
 413          # De-select for analysis those spins who have not been clustered 
 414          for free_spin in cdp.clustering['free spins']: 
 415              print("Deselecting free spin %s"%free_spin) 
 416              self.interpreter.deselect.spin(spin_id=free_spin, change_all=False) 
 417   
 418   
 419          #Paper         reference values 
 420          #              Resi   Resn         R1_rad_s   R1err_rad_s   R2_rad_s   R2err_rad_s   kEX_rad_s      kEXerr_rad_s  phi_rad2_s2     phierr_rad2_s2    phi_ppm2         phierr_ppm2 
 421          # Scaling rad2_s2 to ppm2: scaling_rad2_s2 = frequency_to_ppm(frq=1/(2*pi), B0=cdp.spectrometer_frq_list[0], isotope='15N')**2 = 3.85167990165e-06 
 422          ds.ref = dict() 
 423          ds.ref[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 424          ds.ref[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 425          ds.ref[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 426          ds.ref[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 427          ds.ref[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 428          ds.ref[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 429          ds.ref[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 430          ds.ref[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 431          ds.ref[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 432          ds.ref[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 433          ds.ref[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 434          ds.ref[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 435          ds.ref[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 436          ds.ref[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 437          ds.ref[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 438   
 439          ds.guess = dict() 
 440          ds.guess[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 441          ds.guess[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 442          ds.guess[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 443          ds.guess[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 444          ds.guess[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 445          ds.guess[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 446          ds.guess[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 447          ds.guess[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 448          ds.guess[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 449          ds.guess[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 450          ds.guess[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 451          ds.guess[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 452          ds.guess[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 453          ds.guess[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 454          ds.guess[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 455   
 456          # Assign guess values. 
 457          for spin, spin_id in spin_loop(return_id=True): 
 458              if spin_id in cluster_ids: 
 459                  print("spin_id %s in cluster ids"%(spin_id)) 
 460                  spin.kex = ds.guess[spin_id][6] 
 461                  spin.phi_ex = ds.guess[spin_id][10] 
 462              else: 
 463                  print("spin_id %s NOT in cluster ids"%(spin_id)) 
 464   
 465          if read_R1: 
 466              # Read the R1 data 
 467              self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
 468   
 469   
 470 -    def setup_hansen_cpmg_data(self, model=None): 
 471          """Set up the data for the test_hansen_cpmg_data_*() system tests. 
 472   
 473          @keyword model: The name of the model which will be tested. 
 474          @type model:    str 
 475          """ 
 476   
 477          # Create the data pipe and load the base data. 
 478          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 479          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 480          self.interpreter.results.read(data_path+sep+'base_pipe') 
 481          self.interpreter.deselect.spin(':4') 
 482   
 483          # Set the nuclear isotope data. 
 484          self.interpreter.spin.isotope('15N') 
 485   
 486          # Create the R2eff data pipe and load the results. 
 487          self.interpreter.pipe.create(pipe_name='R2eff - relax_disp', pipe_type='relax_disp') 
 488          self.interpreter.pipe.switch(pipe_name='R2eff - relax_disp') 
 489          self.interpreter.results.read(data_path+sep+'r2eff_pipe') 
 490          self.interpreter.deselect.spin(':4') 
 491   
 492          # The model data pipe. 
 493          pipe_name = "%s - relax_disp" % model 
 494          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 495          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 496   
 497          # Set the model. 
 498          self.interpreter.relax_disp.select_model(model=model) 
 499   
 500          # Copy the data. 
 501          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to=pipe_name, param='r2eff') 
 502   
 503   
 504 -    def setup_kteilum_fmpoulsen_makke_cpmg_data(self, model=None, expfolder=None): 
 505          """Set up the data for the test_kteilum_fmpoulsen_makke_cpmg_data_*() system tests. 
 506   
 507          @keyword model: The name of the model which will be tested. 
 508          @type model:    str 
 509          """ 
 510   
 511          # Create the data pipe and load the base data. 
 512          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder 
 513          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 514          self.interpreter.results.read(data_path+sep+'ini_setup_trunc') 
 515   
 516          # Create the R2eff data pipe and load the results. 
 517          self.interpreter.pipe.create(pipe_name='R2eff', pipe_type='relax_disp') 
 518          self.interpreter.pipe.switch(pipe_name='R2eff') 
 519          self.interpreter.results.read(data_path+sep+'r2eff_pipe_trunc') 
 520   
 521          # The model data pipe. 
 522          pipe_name = "%s - relax_disp" % model 
 523          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 524          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 525   
 526          # Set the model. 
 527          self.interpreter.relax_disp.select_model(model=model) 
 528   
 529          # Copy the data. 
 530          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 531   
 532   
 533 -    def setup_korzhnev_2005_data(self, data_list=[]): 
 534          """Set up the data for the test_korzhnev_2005_data_*() system tests using the 'NS MMQ 2-site' model. 
 535   
 536          This loads the proton-heteronuclear SQ, ZQ, DQ, and MQ (MMQ) data from: 
 537   
 538              - Dmitry M. Korzhnev, Philipp Neudecker, Anthony Mittermaier, Vladislav Yu. Orekhov, and Lewis E. Kay (2005)  Multiple-site exchange in proteins studied with a suite of six NMR relaxation dispersion experiments: An application to the folding of a Fyn SH3 domain mutant.  127, 15602-15611 (U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}). 
 539   
 540          It consists of the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
 541   
 542   
 543          @keyword data_list: The list of data to load.  It can contain 'SQ', '1H SQ', 'ZQ', 'DQ', 'MQ', and '1H MQ'. 
 544          @type data_list:    list of str 
 545          """ 
 546   
 547          # Create the data pipe and load the base data. 
 548          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
 549          self.interpreter.pipe.create(pipe_name='Korzhnev et al., 2005', pipe_type='relax_disp') 
 550   
 551          # Create the spin system. 
 552          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
 553          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
 554          self.interpreter.spin.element('H', spin_id='@H') 
 555          self.interpreter.spin.element('N', spin_id='@N') 
 556          self.interpreter.spin.isotope('1H', spin_id='@H') 
 557          self.interpreter.spin.isotope('15N', spin_id='@N') 
 558   
 559          # Define the magnetic dipole-dipole relaxation interaction. 
 560          self.interpreter.interatom.define(spin_id1=':9@N', spin_id2=':9@H', direct_bond=True) 
 561   
 562          # The spectral data - experiment ID, R2eff file name, experiment type, spin ID string, spectrometer frequency in Hertz, relaxation time. 
 563          data = [ 
 564              ['1H SQ', '1H_SQ_CPMG_500_MHz',  'hs_500.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 500e6, 0.03], 
 565              ['1H SQ', '1H_SQ_CPMG_600_MHz',  'hs_600.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 600e6, 0.03], 
 566              ['1H SQ', '1H_SQ_CPMG_800_MHz',  'hs_800.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 800e6, 0.03], 
 567              ['SQ',    '15N_SQ_CPMG_500_MHz', 'ns_500.res', EXP_TYPE_CPMG_SQ,        ':9@N', 500e6, 0.04], 
 568              ['SQ',    '15N_SQ_CPMG_600_MHz', 'ns_600.res', EXP_TYPE_CPMG_SQ,        ':9@N', 600e6, 0.04], 
 569              ['SQ',    '15N_SQ_CPMG_800_MHz', 'ns_800.res', EXP_TYPE_CPMG_SQ,        ':9@N', 800e6, 0.04], 
 570              ['DQ',    '15N_DQ_CPMG_500_MHz', 'dq_500.res', EXP_TYPE_CPMG_DQ,        ':9@N', 500e6, 0.03], 
 571              ['DQ',    '15N_DQ_CPMG_600_MHz', 'dq_600.res', EXP_TYPE_CPMG_DQ,        ':9@N', 600e6, 0.03], 
 572              ['DQ',    '15N_DQ_CPMG_800_MHz', 'dq_800.res', EXP_TYPE_CPMG_DQ,        ':9@N', 800e6, 0.03], 
 573              ['ZQ',    '15N_ZQ_CPMG_500_MHz', 'zq_500.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 500e6, 0.03], 
 574              ['ZQ',    '15N_ZQ_CPMG_600_MHz', 'zq_600.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 600e6, 0.03], 
 575              ['ZQ',    '15N_ZQ_CPMG_800_MHz', 'zq_800.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 800e6, 0.03], 
 576              ['1H MQ', '1H_MQ_CPMG_500_MHz',  'hm_500.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 500e6, 0.02], 
 577              ['1H MQ', '1H_MQ_CPMG_600_MHz',  'hm_600.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 600e6, 0.02], 
 578              ['1H MQ', '1H_MQ_CPMG_800_MHz',  'hm_800.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 800e6, 0.02], 
 579              ['MQ',    '15N_MQ_CPMG_500_MHz', 'nm_500.res', EXP_TYPE_CPMG_MQ,        ':9@N', 500e6, 0.02], 
 580              ['MQ',    '15N_MQ_CPMG_600_MHz', 'nm_600.res', EXP_TYPE_CPMG_MQ,        ':9@N', 600e6, 0.02], 
 581              ['MQ',    '15N_MQ_CPMG_800_MHz', 'nm_800.res', EXP_TYPE_CPMG_MQ,        ':9@N', 800e6, 0.02] 
 582          ] 
 583          cpmg_frqs_1h_sq = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
 584          cpmg_frqs_sq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 585          cpmg_frqs_dq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 586          cpmg_frqs_zq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 587          cpmg_frqs_1h_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 1000.0, 1500.0, 2000.0, 2500.0] 
 588          cpmg_frqs_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 589   
 590          # Loop over the files, reading in the data. 
 591          for data_type, id, file, exp_type, spin_id, H_frq, relax_time in data: 
 592              # Skip undesired data. 
 593              if data_type not in data_list: 
 594                  continue 
 595   
 596              # Alias the CPMG frequencies. 
 597              if data_type == 'SQ': 
 598                  cpmg_frqs = cpmg_frqs_sq 
 599              elif data_type == '1H SQ': 
 600                  cpmg_frqs = cpmg_frqs_1h_sq 
 601              elif data_type == 'DQ': 
 602                  cpmg_frqs = cpmg_frqs_dq 
 603              elif data_type == 'ZQ': 
 604                  cpmg_frqs = cpmg_frqs_zq 
 605              elif data_type == '1H MQ': 
 606                  cpmg_frqs = cpmg_frqs_1h_mq 
 607              elif data_type == 'MQ': 
 608                  cpmg_frqs = cpmg_frqs_mq 
 609   
 610              # Loop over each CPMG frequency. 
 611              for cpmg_frq in cpmg_frqs: 
 612                  # The id. 
 613                  new_id = "%s_%s" % (id, cpmg_frq) 
 614   
 615                  # Set the NMR field strength. 
 616                  self.interpreter.spectrometer.frequency(id=new_id, frq=H_frq) 
 617   
 618                  # Set the relaxation dispersion experiment type. 
 619                  self.interpreter.relax_disp.exp_type(spectrum_id=new_id, exp_type=exp_type) 
 620   
 621                  # Relaxation dispersion CPMG constant time delay T (in s). 
 622                  self.interpreter.relax_disp.relax_time(spectrum_id=new_id, time=relax_time) 
 623   
 624                  # Set the CPMG frequency. 
 625                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=new_id, cpmg_frq=cpmg_frq) 
 626   
 627              # Read the R2eff data. 
 628              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
 629   
 630          # Change the model. 
 631          self.interpreter.relax_disp.select_model('NS MMQ 2-site') 
 632   
 633   
 634 -    def setup_sod1wt_t25(self, pipe_name, pipe_type, pipe_name_r2eff, select_spin_index): 
 635          """Setup of data SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
 636   
 637          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
 638          'SOD1-WT' CPMG data to the CR72 dispersion model. 
 639   
 640          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
 641          Data is for experiment at 25 degree Celcius. 
 642          """ 
 643   
 644          # Create the data pipe and load the base data. 
 645          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'sod1wt_t25' 
 646   
 647          # Set experiment settings. sfrq, time_T2, ncyc 
 648          Exps = [ 
 649          ["600MHz", "Z_A", 599.8908617*1E6, 0.06, [28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 50, 18, 40, 6, 12, 0, 24], ["Z_A1", "Z_A15"] ], 
 650          ["500MHz", "Z_B", 499.862139*1E6, 0.04, [20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0], ["Z_B1", "Z_B18"] ] ] 
 651   
 652          # Create base pipe 
 653          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 654   
 655          # Loop throug experiments 
 656          id_lists = [] 
 657          for folder, key, sfrq, time_T2, ncycs, rep_ncyss in Exps: 
 658              # Read spins 
 659              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 660              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 661   
 662              # Make spectrum id list 
 663              id_list = list(key+str(i) for i in range(len(ncycs))) 
 664              id_lists.append(id_list) 
 665   
 666              # Read intensities 
 667              self.interpreter.spectrum.read_intensities(file="128_FT.ser", dir=data_path+sep+folder, int_method='height', spectrum_id=id_list, int_col=list(range(len(id_list))) ) 
 668   
 669              # Loop over experiments 
 670              for i in range(len(ncycs)): 
 671                  ncyc = ncycs[i] 
 672                  vcpmg = ncyc/time_T2 
 673   
 674                  # Test if spectrum is a reference 
 675                  if float(vcpmg) == 0.0: 
 676                      vcpmg = None 
 677                  else: 
 678                      vcpmg = round(float(vcpmg), 3) 
 679   
 680                  # Set current id 
 681                  current_id = id_list[i] 
 682   
 683                  # Set the current experiment type. 
 684                  self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
 685   
 686                  # Set the NMR field strength of the spectrum. 
 687                  self.interpreter.spectrometer.frequency(id=current_id, frq=sfrq, units='Hz') 
 688   
 689                  # Relaxation dispersion CPMG constant time delay T (in s). 
 690                  self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
 691   
 692                  # Set the relaxation dispersion CPMG frequencies. 
 693                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
 694   
 695          # Define replicated 
 696          self.interpreter.spectrum.replicated(spectrum_ids=Exps[0][5]) 
 697          self.interpreter.spectrum.replicated(spectrum_ids=Exps[1][5]) 
 698   
 699          # Perform error analysis 
 700          self.interpreter.spectrum.error_analysis(subset=id_lists[0]) 
 701          self.interpreter.spectrum.error_analysis(subset=id_lists[1]) 
 702   
 703          # Define isotope 
 704          self.interpreter.spin.isotope(isotope='15N') 
 705   
 706          ############# 
 707   
 708          # Define the 64 residues which was used for Global fitting 
 709          glob_assn = ["G10N-H", "D11N-H", "Q15N-H", "G16N-H", "G37N-H", "G41N-H", "L42N-H", "H43N-H", "H46N-H", "V47N-H", "E49N-H", 
 710          "E50N-H", "E51N-H", "N53N-H", "T54N-H", "G56N-H", "C57N-H", "T58N-H", "G61N-H", "H63aN-H", "F64aN-H", "N65aN-H", 
 711          "L67N-H", "S68N-H", "K70N-H", "G72N-H", "G73N-H", "K75N-H", "E78N-H", "R79N-H", "H80N-H", "V81N-H", "G82N-H", 
 712          "G85N-H", "N86N-H", "V87N-H", "S102N-H", "V103N-H", "I104N-H", "S105N-H", "A111N-H", "I112N-H", "R115N-H", 
 713          "V118N-H", "E121N-H", "A123N-H", "L126N-H", "G127N-H", "K128N-H", "G129N-H", "G130N-H", "N131N-H", "E133N-H", 
 714          "S134N-H", "T135N-H", "T137N-H", "G138N-H", "N139N-H", "A140N-H", "G141N-H", "S142N-H", "R143N-H", "C146N-H", "G147N-H"] 
 715   
 716          # Test number of global 
 717          self.assertEqual(64, len(glob_assn )) 
 718   
 719          ## Turn assignments into relax spin ids. 
 720          # Define regular expression search 
 721          r = re.compile("([a-zA-Z]+)([0-9]+)([a-zA-Z]+)") 
 722   
 723          # Create list to hold regular expression search 
 724          relax_glob_ids = [] 
 725   
 726          # Loop over assignments 
 727          for assn in glob_assn: 
 728              # Make match for the regular search 
 729              m = r.match(assn) 
 730              # Convert to relax spin string 
 731              relax_string = ":%s@%s"%(m.group(2), m.group(3)) 
 732   
 733              # Save the relax spin string and the regular search 
 734              relax_glob_ids.append([m.group(0), m.group(1), m.group(2), m.group(3), relax_string]) 
 735   
 736          ############# Deselect all spins, and select few spins 
 737   
 738          ## Deselect all spins, and select a few for analysis 
 739          self.interpreter.deselect.all() 
 740   
 741          # Select few spins 
 742          for i in select_spin_index: 
 743              self.interpreter.select.spin(spin_id=relax_glob_ids[i][4], change_all=False) 
 744   
 745          ############## 
 746   
 747          # Prepare for R2eff calculation 
 748          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 749          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 750   
 751          # Select model for points calculation 
 752          MODEL = "R2eff" 
 753          self.interpreter.relax_disp.select_model(model=MODEL) 
 754          # Calculate R2eff values 
 755          self.interpreter.minimise.calculate(verbosity=1) 
 756   
 757   
 758 -    def setup_missing_r1_spins(self): 
 759          """Function for setting up a few spins for the given pipe.""" 
 760   
 761          # Path to file. 
 762          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 763   
 764          # File with spins. 
 765          file = open(data_path+sep+'R1_fitted_values.txt') 
 766          lines = file.readlines() 
 767          file.close() 
 768   
 769          for i, line in enumerate(lines): 
 770              # Make the string test 
 771              line_split = line.split() 
 772   
 773              if line_split[0] == "#": 
 774                  continue 
 775   
 776              mol_name = line_split[0] 
 777              mol_name = None 
 778              res_num = int(line_split[1]) 
 779              res_name = line_split[2] 
 780              spin_num = line_split[3] 
 781              spin_num = None 
 782              spin_name = line_split[4] 
 783   
 784              # Create the spin. 
 785              self.interpreter.spin.create(spin_name=spin_name, spin_num=spin_num, res_name=res_name, res_num=res_num, mol_name=mol_name) 
 786   
 787   
 788 -    def setup_tp02_data_to_ns_r1rho_2site(self, clustering=False): 
 789          """Setup data for the test of relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
 790   
 791          # Reset. 
 792          self.interpreter.reset() 
 793   
 794          # Create the data pipe and load the base data. 
 795          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
 796          self.interpreter.state.load(data_path+sep+'r2eff_values') 
 797   
 798          # The model data pipe. 
 799          model = 'NS R1rho 2-site' 
 800          pipe_name = "%s - relax_disp" % model 
 801          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 802          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 803   
 804          # Set the model. 
 805          self.interpreter.relax_disp.select_model(model=model) 
 806   
 807          # Copy the data. 
 808          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 809   
 810          # Alias the spins. 
 811          spin1 = cdp.mol[0].res[0].spin[0] 
 812          spin2 = cdp.mol[0].res[1].spin[0] 
 813   
 814          # The R20 keys. 
 815          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
 816          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
 817   
 818          # Set the initial parameter values. 
 819          spin1.r2 = {r20_key1: 9.9963793866185, r20_key2: 15.0056724422684} 
 820          spin1.pA = 0.779782428085762 
 821          spin1.dw = 7.57855284496424 
 822          spin1.kex = 1116.7911285203 
 823          spin2.r2 = {r20_key1: 11.9983346935434, r20_key2: 18.0076097513337} 
 824          spin2.pA = 0.826666229688602 
 825          spin2.dw = 9.5732624231366 
 826          spin2.kex = 1380.46162655657 
 827   
 828          # Test the values when clustering. 
 829          if clustering: 
 830              self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-100") 
 831   
 832          # Low precision optimisation. 
 833          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
 834   
 835          # Printout. 
 836          print("\n\nOptimised parameters:\n") 
 837          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
 838          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
 839          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
 840          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
 841          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
 842          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
 843          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
 844   
 845   
 846 -    def test_baldwin_synthetic(self): 
 847          """Test synthetic data of Andrew J. Baldwin B14 model  whereby the simplification R20A = R20B is assumed. 
 848   
 849          Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
 850   
 851          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>} with R20A, R20B = 2. rad/s. 
 852          """ 
 853   
 854          # The path to the data files. 
 855          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
 856   
 857          # Create pipe 
 858          pipe_name = 'base pipe' 
 859          pipe_type = 'relax_disp' 
 860          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
 861   
 862          # Create base pipe 
 863          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 864   
 865          # Generate the sequence. 
 866          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
 867   
 868          # Define the isotope. 
 869          self.interpreter.spin.isotope('1H', spin_id='@H') 
 870   
 871          # Build the experiment IDs. 
 872          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
 873          ncycs = [2, 4, 8, 10, 20, 40, 500] 
 874          ids = [] 
 875          for ncyc in ncycs: 
 876              ids.append('CPMG_%s' % ncyc) 
 877   
 878          print("\n\nThe experiment IDs are %s." % ids) 
 879   
 880          # Set up the metadata for the experiments. 
 881          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
 882          sfrq = 200. * 1E6 
 883   
 884          # Total time of CPMG block. 
 885          Trelax = 0.04 
 886   
 887          # First set the 
 888          for i in range(len(ids)): 
 889              id = ids[i] 
 890              # Set the spectrometer frequency. 
 891              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
 892   
 893              # Set the experiment type. 
 894              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
 895   
 896              # Set the relaxation dispersion CPMG constant time delay T (in s). 
 897              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
 898   
 899              # Set the relaxation dispersion CPMG frequencies. 
 900              ncyc = ncycs[i] 
 901              nu_cpmg = ncyc / Trelax 
 902              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
 903   
 904          # Prepare for R2eff reading. 
 905          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 906          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 907   
 908          # Try reading the R2eff file. 
 909          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_r2a_eq_r2b_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
 910   
 911          # Check the global data. 
 912          data = [ 
 913              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
 914              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
 915              ['dispersion_points', len(ncycs)], 
 916              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
 917              ['exp_type_list', ['SQ CPMG']], 
 918              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
 919              ['spectrometer_frq_count', 1], 
 920              ['spectrometer_frq_list', [sfrq]], 
 921              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
 922          ] 
 923          for name, value in data: 
 924              # Does it exist? 
 925              self.assert_(hasattr(cdp, name)) 
 926   
 927              # Check the object. 
 928              obj = getattr(cdp, name) 
 929              if not isinstance(data, dict): 
 930                  self.assertEqual(obj, value) 
 931   
 932              # Check the global dictionary data. 
 933              else: 
 934                  for id in ids: 
 935                      self.assertEqual(obj[id], value[id]) 
 936   
 937          # Check the spin data. 
 938          n_data = [ 
 939              [ 50.000000, 10.367900, 0.1], 
 940              [ 100.000000, 10.146849, 0.1], 
 941              [ 200.000000, 9.765987, 0.1], 
 942              [ 250.000000, 9.409789, 0.1], 
 943              [ 500.000000, 5.829819, 0.1], 
 944              [ 1000.000000, 3.191928, 0.1], 
 945              [ 12500.000000, 2.008231, 0.1] 
 946          ] 
 947          for disp_point, value, error in n_data: 
 948              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
 949              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
 950              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
 951   
 952          # Generate r20 key. 
 953          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
 954   
 955          ## Now prepare for MODEL calculation. 
 956          MODEL = "B14" 
 957   
 958          # Change pipe. 
 959          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
 960          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
 961          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 962   
 963          # Then select model. 
 964          self.interpreter.relax_disp.select_model(model=MODEL) 
 965   
 966          # Store grid and minimisations results. 
 967          grid_results = [] 
 968          mini_results = [] 
 969   
 970          # The grid search size (the number of increments per dimension). 
 971          # If None, use the default values. 
 972          #GRID = None 
 973          GRID = 13 
 974          # Perform Grid Search. 
 975          if GRID: 
 976              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
 977              # This speeds it up considerably. 
 978              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
 979   
 980              # Then do grid search. 
 981              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
 982   
 983              # If no Grid search, set the default values. 
 984          else: 
 985              for param in MODEL_PARAMS[MODEL]: 
 986                  self.interpreter.value.set(param=param, index=None) 
 987                  # Do a grid search, which will store the chi2 value. 
 988              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
 989   
 990          # Store result. 
 991          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
 992              grid_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
 993   
 994          ## Now do minimisation. 
 995          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
 996          set_func_tol = 1e-10 
 997          set_max_iter = 1000 
 998          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
 999   
1000          # Store result. 
1001          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1002              mini_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1003   
1004          # Print results. 
1005          for i in range(len(grid_results)): 
1006              g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1007              m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1008              print("GRID %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1009              print("MIN  %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1010   
1011          # Reference values from Baldwin.py. 
1012          # Exchange rate = k+ + k- (s-1) 
1013          kex = 1000. 
1014          # Fractional population of excited state k+/kex 
1015          pb = 0.01 
1016          # deltaOmega in ppm 
1017          dw_ppm = 2. 
1018          #relaxation rate of ground (s-1) 
1019          R2g = 2. 
1020          #relaxation rate of excited (s-1) 
1021          R2e = 2. 
1022   
1023          # Test the parameters which created the data. 
1024          # This is for the 1H spin. 
1025          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key], R2g, 6) 
1026   
1027          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1028          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 8) 
1029          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 3) 
1030   
1031   
1032 -    def test_baldwin_synthetic_full(self): 
1033          """Test synthetic data of Andrew J. Baldwin B14 model. Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
1034   
1035          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>}. 
1036          """ 
1037   
1038          # The path to the data files. 
1039          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
1040   
1041          # Create pipe 
1042          pipe_name = 'base pipe' 
1043          pipe_type = 'relax_disp' 
1044          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
1045   
1046          # Create base pipe 
1047          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
1048   
1049          # Generate the sequence. 
1050          # Generate both a 1H spin, and 15N spin. 
1051          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
1052   
1053          # Define the isotope. 
1054          self.interpreter.spin.isotope('1H', spin_id='@H') 
1055   
1056          # Build the experiment IDs. 
1057          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
1058          ncycs = [2, 4, 8, 10, 20, 40, 500] 
1059          ids = [] 
1060          for ncyc in ncycs: 
1061              ids.append('CPMG_%s' % ncyc) 
1062   
1063          print("\n\nThe experiment IDs are %s." % ids) 
1064   
1065          # Set up the metadata for the experiments. 
1066          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
1067          sfrq = 200. * 1E6 
1068   
1069          # Total time of CPMG block. 
1070          Trelax = 0.04 
1071   
1072          # First set the 
1073          for i in range(len(ids)): 
1074              id = ids[i] 
1075              # Set the spectrometer frequency. 
1076              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
1077   
1078              # Set the experiment type. 
1079              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
1080   
1081              # Set the relaxation dispersion CPMG constant time delay T (in s). 
1082              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
1083   
1084              # Set the relaxation dispersion CPMG frequencies. 
1085              ncyc = ncycs[i] 
1086              nu_cpmg = ncyc / Trelax 
1087              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
1088   
1089          # Prepare for R2eff reading. 
1090          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
1091          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
1092   
1093          # Try reading the R2eff file. 
1094          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
1095   
1096          # Check the global data. 
1097          data = [ 
1098              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
1099              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
1100              ['dispersion_points', len(ncycs)], 
1101              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
1102              ['exp_type_list', ['SQ CPMG']], 
1103              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
1104              ['spectrometer_frq_count', 1], 
1105              ['spectrometer_frq_list', [sfrq]], 
1106              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
1107          ] 
1108          for name, value in data: 
1109              # Does it exist? 
1110              self.assert_(hasattr(cdp, name)) 
1111   
1112              # Check the object. 
1113              obj = getattr(cdp, name) 
1114              if not isinstance(data, dict): 
1115                  self.assertEqual(obj, value) 
1116   
1117              # Check the global dictionary data. 
1118              else: 
1119                  for id in ids: 
1120                      self.assertEqual(obj[id], value[id]) 
1121   
1122          # Check the spin data. 
1123          n_data = [ 
1124              [ 50.000000, 10.286255, 0.1], 
1125              [ 100.000000, 10.073083, 0.1], 
1126              [ 200.000000, 9.692746, 0.1], 
1127              [ 250.000000, 9.382441, 0.1], 
1128              [ 500.000000, 6.312396, 0.1], 
1129              [ 1000.000000, 3.957029, 0.1], 
1130              [ 12500.000000, 2.880420, 0.1] 
1131          ] 
1132          for disp_point, value, error in n_data: 
1133              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
1134              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
1135              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
1136   
1137          # Generate r20 key. 
1138          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
1139   
1140          ## Now prepare for MODEL calculation. 
1141          MODEL = "B14 full" 
1142   
1143          # Change pipe. 
1144          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
1145          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
1146          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
1147   
1148          # Then select model. 
1149          self.interpreter.relax_disp.select_model(model=MODEL) 
1150   
1151          # Store grid and minimisations results. 
1152          grid_results = [] 
1153          mini_results = [] 
1154          clust_results = [] 
1155   
1156          # The grid search size (the number of increments per dimension). 
1157          # If None, use the default values. 
1158          #GRID = None 
1159          GRID = 13 
1160          # Perform Grid Search. 
1161          if GRID: 
1162              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
1163              # This speeds it up considerably. 
1164              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
1165   
1166              # Then do grid search. 
1167              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
1168   
1169              # If no Grid search, set the default values. 
1170          else: 
1171              for param in MODEL_PARAMS[MODEL]: 
1172                  self.interpreter.value.set(param=param, index=None) 
1173                  # Do a grid search, which will store the chi2 value. 
1174              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
1175   
1176          # Store result. 
1177          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1178              grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1179   
1180          ## Now do minimisation. 
1181          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1182          set_func_tol = 1e-11 
1183          set_max_iter = 10000 
1184          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1185   
1186          # Store result. 
1187          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1188              mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1189   
1190          print("\n# Now print before and after minimisation-\n") 
1191   
1192          # Print results. 
1193          for i in range(len(grid_results)): 
1194              g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1195              m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1196              print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1197              print("MIN  %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1198   
1199          # Reference values from Baldwin.py. 
1200          # Exchange rate = k+ + k- (s-1) 
1201          kex = 1000. 
1202          # Fractional population of excited state k+/kex 
1203          pb = 0.01 
1204          # deltaOmega in ppm 
1205          dw_ppm = 2. 
1206          #relaxation rate of ground (s-1) 
1207          R2g = 2. 
1208          #relaxation rate of excited (s-1) 
1209          R2e = 100. 
1210   
1211          # Test the parameters which created the data. 
1212          # This is for the 1H spin. 
1213          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key], R2g, 3) 
1214          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key]/100, R2e/100, 3) 
1215   
1216          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1217          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6) 
1218          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex/1000, kex/1000, 2) 
1219   
1220   
1221 -    def x_test_bmrb_sub_cpmg(self): 
1222          """U{Task #7858: <https://gna.org/task/?7858>} Make it possible to submit CPMG experiments for BMRB. 
1223          This uses CPMG data from: 
1224              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE. 
1225                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
1226                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, DOI 10.1002/prot.22886 
1227          """ 
1228   
1229          # Define path to data  
1230          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
1231   
1232          # Read data. 
1233          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
1234   
1235          # Set element 
1236          self.interpreter.spin.element(element='N', spin_id=':*@N', force=False) 
1237          #self.interpreter.spin.isotope(isotope='15N', spin_id=':*@N', force=False) 
1238          # Rename molecule from None to 'HEWL' 
1239          self.interpreter.molecule.name(mol_id=None, name='HEWL', force=True) 
1240          self.interpreter.molecule.type(mol_id='#HEWL', type='protein', force=False) 
1241   
1242          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1243              print(spin_id) 
1244              if resn == 'C': 
1245                  print(resi, resn) 
1246   
1247          # Select the thiol state of the system. 
1248          # 'all disulfide bound', 'all free', 'all other bound', 'disulfide and other bound', 'free and disulfide bound', 'free and other bound', 'free disulfide and other bound', 'not available', 'not present', 'not reported', 'unknown' 
1249          self.interpreter.bmrb.thiol_state(state='not reported') 
1250   
1251          # relax_data.temp_calibration(ri_id=None, method=None) 
1252   
1253          # Call display of bmrb. 
1254          self.interpreter.bmrb.display() 
1255   
1256   
1257 -    def test_bug_21081_disp_cluster_fail(self): 
1258          """U{Bug #21081<https://gna.org/bugs/?21081>} catch, the failure of a cluster analysis when spins are deselected.""" 
1259   
1260          # Clear the data store. 
1261          self.interpreter.reset() 
1262   
1263          # Load the state. 
1264          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21081_disp_cluster_fail.bz2' 
1265          self.interpreter.state.load(state, force=True) 
1266   
1267          # Model selection - to catch the failure. 
1268          self.interpreter.model_selection(method='AIC', modsel_pipe='final', bundle='relax_disp', pipes=['No Rex', 'CR72']) 
1269   
1270   
1271 -    def test_bug_21460_disp_cluster_fail(self): 
1272          """U{Bug #21460<https://gna.org/bugs/?21460>} catch, the failure due to a spectrometer frequency having no relaxation data.""" 
1273   
1274          # Clear the data store. 
1275          self.interpreter.reset() 
1276   
1277          # Load the state. 
1278          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21460_bad_fields.bz2' 
1279          self.interpreter.state.load(state, force=True) 
1280   
1281          # Execute the auto-analysis (fast). 
1282          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1283          relax_disp.Relax_disp.opt_max_iterations = 1000 
1284          relax_disp.Relax_disp(pipe_name="origin - relax_disp (Thu Jan  2 13:46:44 2014)", pipe_bundle="relax_disp (Thu Jan  2 13:46:44 2014)", results_dir=self.tmpdir, models=['R2eff', 'No Rex', 'CR72', 'NS CPMG 2-site expanded'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1285   
1286   
1287 -    def test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp(self): 
1288          """U{Bug #21665<https://gna.org/bugs/?21344>} catch, the failure of an analysis of a sparse acquired R1rho dataset with missing combinations of time and spin-lock field strengths using auto_analysis.""" 
1289   
1290          # Clear the data store. 
1291          self.interpreter.reset() 
1292   
1293          # Load the state. 
1294          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
1295          self.interpreter.state.load(state, force=True) 
1296   
1297          # Execute the auto-analysis (fast). 
1298          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1299          relax_disp.Relax_disp.opt_max_iterations = 1000 
1300          relax_disp.Relax_disp(pipe_name='base pipe', pipe_bundle='relax_disp', results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1301   
1302   
1303 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_calc(self): 
1304          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using minimise.calculate().""" 
1305   
1306          # Clear the data store. 
1307          self.interpreter.reset() 
1308   
1309          # Load the state. 
1310          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1311          self.interpreter.state.load(state, force=True) 
1312   
1313          # Run the calculation. 
1314          self.interpreter.minimise.calculate(verbosity=1) 
1315   
1316   
1317 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_relax_disp(self): 
1318          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times using auto_analysis.""" 
1319   
1320          # Clear the data store. 
1321          self.interpreter.reset() 
1322   
1323          # Load the state. 
1324          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1325          self.interpreter.state.load(state, force=True) 
1326   
1327          # Execute the auto-analysis (fast). 
1328          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1329          relax_disp.Relax_disp.opt_max_iterations = 1000 
1330          relax_disp.Relax_disp(pipe_name="compare_128_FT_R2eff", pipe_bundle="cpmg_disp_sod1d90a", results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1331   
1332   
1333 -    def test_bug_21715_clustered_indexerror(self): 
1334          """Catch U{bug #21715<https://gna.org/bugs/?21715>}, the failure of a clustered auto-analysis due to an IndexError.""" 
1335   
1336          # Clear the data store. 
1337          self.interpreter.reset() 
1338   
1339          # Load the state. 
1340          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'state.bz2' 
1341          self.interpreter.state.load(state, force=True) 
1342   
1343          # Execute the auto-analysis (fast). 
1344          pre_run_dir = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'non_clustered' 
1345          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1346          relax_disp.Relax_disp.opt_max_iterations = 1000 
1347          relax_disp.Relax_disp(pipe_name='origin - relax_disp (Sun Feb 23 19:36:51 2014)', pipe_bundle='relax_disp (Sun Feb 23 19:36:51 2014)', results_dir=self.tmpdir, models=['R2eff', 'No Rex'], grid_inc=11, mc_sim_num=2, modsel='AIC', pre_run_dir=pre_run_dir, insignificance=1.0, numeric_only=True, mc_sim_all_models=False, eliminate=True) 
1348   
1349   
1350 -    def test_bug_22146_unpacking_r2a_r2b_cluster_B14(self): 
1351          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered B14 full analysis.""" 
1352   
1353          # Base data setup. 
1354          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='B14_full', model_analyse = MODEL_B14_FULL) 
1355   
1356   
1357 -    def test_bug_22146_unpacking_r2a_r2b_cluster_CR72(self): 
1358          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered CR72 full analysis.""" 
1359   
1360          # Base data setup. 
1361          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='CR72_full', model_analyse = MODEL_CR72_FULL) 
1362   
1363   
1364 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_3D(self): 
1365          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE 3D full analysis.""" 
1366   
1367          # Base data setup. 
1368          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_3d_full', model_analyse = MODEL_NS_CPMG_2SITE_3D_FULL) 
1369   
1370   
1371 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_STAR(self): 
1372          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE STAR full analysis.""" 
1373   
1374          # Base data setup. 
1375          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_star_full', model_analyse = MODEL_NS_CPMG_2SITE_STAR_FULL, places = 4) 
1376   
1377   
1378 -    def test_bug_22477_grace_write_k_AB_mixed_analysis(self): 
1379          """Catch U{bug #22146<https://gna.org/bugs/?22477>}, the failure of issuing: grace.write(x_data_type='res_num', y_data_type=param) for a mixed CPMG analysis.""" 
1380   
1381          # Clear the data store. 
1382          self.interpreter.reset() 
1383   
1384          # Load the state. 
1385          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22477_grace_write_k_AB_mixed_analysis'+sep+'bug_22477_results.bz2' 
1386          self.interpreter.state.load(state, force=True) 
1387   
1388          param = 'k_AB' 
1389   
1390          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1391              print(spin_id, spin.params) 
1392              if param in spin.params: 
1393                  print(spin_id, spin.k_AB, spin.k_AB_err) 
1394   
1395          # Perform write. 
1396          self.interpreter.grace.write(x_data_type='res_num', y_data_type=param, file='%s.agr'%param, dir=self.tmpdir, force=True) 
1397   
1398   
1399          # Test the header of the value.write  parameter r2. 
1400          param = 'r2' 
1401          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1402   
1403          file = open(self.tmpdir+sep+'%s.out'%param) 
1404          lines = file.readlines() 
1405          file.close() 
1406   
1407          for i, line in enumerate(lines): 
1408              # Make the string test 
1409              line_split = line.split() 
1410              print(line_split) 
1411   
1412              if len(line_split) > 1: 
1413                  # Break at parameter header. 
1414                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1415                      nr_split_header = len(line_split) 
1416                      nr_split_header_i = i 
1417                      break 
1418   
1419          # Call the line after. 
1420          line_split_val = lines[nr_split_header_i + 1].split() 
1421          print(line_split_val) 
1422   
1423          # Assert that the number of columns is equal, plus 1 for "#". 
1424          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1425   
1426          # Test the header of the value.write for parameter r2eff. 
1427          param = 'r2eff' 
1428          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1429   
1430          file = open(self.tmpdir+sep+'%s.out'%param) 
1431          lines = file.readlines() 
1432          file.close() 
1433   
1434          for i, line in enumerate(lines): 
1435              # Make the string test 
1436              line_split = line.split() 
1437              print(line_split) 
1438   
1439              if len(line_split) > 1: 
1440                  # Break at parameter header. 
1441                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1442                      nr_split_header = len(line_split) 
1443                      nr_split_header_i = i 
1444                      break 
1445   
1446          # Call the line after. 
1447          line_split_val = lines[nr_split_header_i + 1].split() 
1448          print(line_split_val) 
1449   
1450          # Assert that the number of columns is equal, plus 1 for "#". 
1451          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1452   
1453   
1454 -    def test_bug_9999_slow_r1rho_r2eff_error_with_mc(self): 
1455          """Catch U{bug #9999<https://gna.org/bugs/?9999>}, The slow optimisation of R1rho R2eff error estimation with Monte Carlo simulations.""" 
1456   
1457          # Define path to data  
1458          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
1459   
1460          # Read data. 
1461          self.interpreter.results.read(prev_data_path + sep + 'results')         
1462   
1463          # Now count number 
1464          graph_nr = 1 
1465          for exp_type, frq, offset, point in loop_exp_frq_offset_point(return_indices=False): 
1466              print("\nGraph nr %i" % graph_nr) 
1467              for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
1468                  print(exp_type, frq, offset, point, time) 
1469              graph_nr += 1 
1470   
1471          ## Possibly do an error analysis. 
1472   
1473          # Check if intensity errors have already been calculated by the user. 
1474          precalc = True 
1475          for spin in spin_loop(skip_desel=True): 
1476              # No structure. 
1477              if not hasattr(spin, 'peak_intensity_err'): 
1478                  precalc = False 
1479                  break 
1480   
1481              # Determine if a spectrum ID is missing from the list. 
1482              for id in cdp.spectrum_ids: 
1483                  if id not in spin.peak_intensity_err: 
1484                      precalc = False 
1485                      break 
1486   
1487          # Skip. 
1488          if precalc: 
1489              print("Skipping the error analysis as it has already been performed.") 
1490   
1491          else: 
1492              # Loop over the spectrometer frequencies. 
1493              for frq in loop_frq(): 
1494                  # Generate a list of spectrum IDs matching the frequency. 
1495                  ids = [] 
1496                  for id in cdp.spectrum_ids: 
1497                      # Check that the spectrometer frequency matches. 
1498                      match_frq = True 
1499                      if frq != None and cdp.spectrometer_frq[id] != frq: 
1500                          match_frq = False 
1501   
1502                      # Add the ID. 
1503                      if match_frq: 
1504                          ids.append(id) 
1505   
1506                  # Run the error analysis on the subset. 
1507                  self.interpreter.spectrum.error_analysis(subset=ids) 
1508   
1509          print("has_exponential_exp_type:", has_exponential_exp_type()) 
1510   
1511          model = 'R2eff' 
1512          self.interpreter.relax_disp.select_model(model) 
1513   
1514          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1515              #delattr(spin, 'r2eff') 
1516              #delattr(spin, 'r2eff_err') 
1517              #delattr(spin, 'i0') 
1518              #delattr(spin, 'i0_err') 
1519              setattr(spin, 'r2eff', {}) 
1520              setattr(spin, 'r2eff_err', {}) 
1521              setattr(spin, 'i0', {}) 
1522              setattr(spin, 'i0_err', {}) 
1523   
1524          # Do Grid Search 
1525          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=21, constraints=True, verbosity=1) 
1526   
1527          # Start dic. 
1528          my_dic = {} 
1529   
1530          # Define counter for maximum elements in the numpy array list 
1531          NE = 0 
1532          NS = 1 
1533          NM = 0 
1534          NO = 0 
1535          ND = 0 
1536          NT = 0 
1537   
1538          for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1539              # Save to counter. 
1540              if ei > NE: 
1541                  NE = ei 
1542              if mi > NM: 
1543                  NM = mi 
1544              if oi > NO: 
1545                  NO = oi 
1546              if di > ND: 
1547                 ND = di 
1548   
1549              for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1550                  # Save to counter. 
1551                  if ti > NT: 
1552                      NT = ti 
1553   
1554          # Add 1 to counter, since index start from 0. 
1555          NE = NE + 1 
1556          NM = NM + 1  
1557          NO = NO + 1 
1558          ND = ND + 1 
1559          NT = NT + 1 
1560   
1561          # Make data array. 
1562          values_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1563          errors_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1564          times_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1565          struct_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1566          param_key_list = [] 
1567   
1568   
1569          # Loop over each spectrometer frequency and dispersion point. 
1570          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1571              # Add key to dic. 
1572              my_dic[spin_id] = {} 
1573   
1574              # Generate spin string. 
1575              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1576   
1577              # Loop over the parameters. 
1578              #print("Grid optimised parameters for spin: %s" % (spin_string)) 
1579   
1580              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1581                  # Generate the param_key. 
1582                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1583   
1584                  # Append key. 
1585                  param_key_list.append(param_key) 
1586   
1587                  # Add key to dic. 
1588                  my_dic[spin_id][param_key] = {} 
1589   
1590                  # Get the value. 
1591                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1592                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1593   
1594                  # Save to dic. 
1595                  my_dic[spin_id][param_key]['R2eff_value_grid'] = R2eff_value 
1596                  my_dic[spin_id][param_key]['i0_value_grid'] = i0_value 
1597   
1598                  ## Now try do a line of best fit by least squares. 
1599                  # The peak intensities, errors and times. 
1600                  values = [] 
1601                  errors = [] 
1602                  times = [] 
1603                  for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1604                      value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1605                      values.append(value) 
1606   
1607                      error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1608                      errors.append(error) 
1609                      times.append(time) 
1610   
1611                      # Save to numpy arrays. 
1612                      values_arr[ei, 0, mi, oi, di, ti] = value 
1613                      errors_arr[ei, 0, mi, oi, di, ti] = error 
1614                      times_arr[ei, 0, mi, oi, di, ti] = time 
1615                      struct_arr[ei, 0, mi, oi, di, ti] = 1.0 
1616   
1617                  # y= A exp(x * k) 
1618                  # w[i] = ln(y[i]) 
1619                  # int[i] = i0 * exp( - times[i] * r2eff); 
1620                  w = log(array(values)) 
1621                  x = - array(times) 
1622                  n = len(times) 
1623   
1624                  b = (sum(x*w) - 1./n * sum(x) * sum(w) ) / ( sum(x**2) - 1./n * (sum(x))**2 ) 
1625                  a = 1./n * sum(w) - b * 1./n * sum(x) 
1626                  R2eff_est = b 
1627                  i0_est = exp(a) 
1628   
1629                  my_dic[spin_id][param_key]['R2eff_est'] = R2eff_est 
1630                  my_dic[spin_id][param_key]['i0_est'] = i0_est 
1631   
1632                  # Print value. 
1633                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1634                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1635   
1636   
1637          # Do minimisation. 
1638          set_func_tol = 1e-25 
1639          set_max_iter = int(1e7) 
1640          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1641   
1642          # Loop over each spectrometer frequency and dispersion point. 
1643          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1644              # Generate spin string. 
1645              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1646   
1647              # Loop over the parameters. 
1648              print("Optimised parameters for spin: %s" % (spin_string)) 
1649   
1650              for exp_type, frq, offset, point in loop_exp_frq_offset_point(): 
1651                  # Generate the param_key. 
1652                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1653   
1654                  # Get the value. 
1655                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1656                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1657   
1658                  # Extract from dic. 
1659                  R2eff_value_grid = my_dic[spin_id][param_key]['R2eff_value_grid'] 
1660                  i0_value_grid = my_dic[spin_id][param_key]['i0_value_grid'] 
1661                  R2eff_est = my_dic[spin_id][param_key]['R2eff_est'] 
1662                  i0_est = my_dic[spin_id][param_key]['i0_est'] 
1663   
1664                  # Print value. 
1665                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1666                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1667   
1668                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'R2eff', "Grid : Min : Estimated:", R2eff_value_grid, R2eff_value, R2eff_est)) 
1669                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'i0', "Grid : Min : Estimated:", i0_value_grid, i0_value, i0_est)) 
1670   
1671          print(NE, NS, NM, NO, ND, NT) 
1672          for param_key in param_key_list: 
1673              print("        '%s'," % param_key) 
1674          print(values_arr.shape) 
1675   
1676          # Save arrays to profiling. 
1677          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep 
1678          #save(data_path + "values_arr", values_arr) 
1679          #save(data_path + "errors_arr", errors_arr) 
1680          #save(data_path + "times_arr", times_arr) 
1681          #save(data_path + "struct_arr", struct_arr) 
1682   
1683   
1684 -    def test_bug_atul_srivastava(self): 
1685          """Test data from Atul Srivastava.  This is a bug missing raising a Relax Error, since the setup points to a situation where the data 
1686          shows it is exponential fitting, but only one time point is added per file. 
1687   
1688          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1718>}: 
1689          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735>}: 
1690          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735/focus=1736>}: 
1691   
1692          """ 
1693   
1694          # Data path. 
1695          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_Atul_Srivastava' 
1696          file = data_path + sep + 'bug_script.py' 
1697   
1698          # Run script. 
1699          self.interpreter.script(file=file, dir=None) 
1700   
1701          # The grid search size (the number of increments per dimension). 
1702          GRID_INC = 11 
1703   
1704          # Check-data. 
1705          ################# 
1706   
1707          # Loop over spins, to see current setup. 
1708          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1709              print(mol_name, resi, resn, spin_id) 
1710   
1711          # Loop over setup. 
1712          for id in cdp.exp_type: 
1713              print(id, cdp.exp_type[id], cdp.spectrometer_frq[id], cdp.spin_lock_offset[id], cdp.spin_lock_nu1[id]) 
1714   
1715   
1716          # Manual minimisation. 
1717          ################# 
1718          if True: 
1719              # Set the model. 
1720              self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
1721   
1722              # Check if intensity errors have already been calculated. 
1723              check_intensity_errors() 
1724   
1725              # Calculate the R2eff values for the fixed relaxation time period data types. 
1726              if cdp.model_type == MODEL_R2EFF and not has_exponential_exp_type(): 
1727                  self.interpreter.minimise.calculate() 
1728   
1729              # Optimise the model. 
1730              else: 
1731                  constraints = False 
1732                  min_algor = 'Newton' 
1733                  self.assertRaises(RelaxError, self.interpreter.minimise.grid_search, inc=GRID_INC) 
1734                  self.assertRaises(RelaxError, self.interpreter.minimise.execute, min_algor=min_algor, constraints=constraints) 
1735   
1736          # Inspect. 
1737          if False: 
1738              # Loop over attributes. 
1739              par_attr_list = ['r2eff', 'i0'] 
1740   
1741              # Collect the estimation data. 
1742              my_dic = {} 
1743              param_key_list = [] 
1744              est_keys = [] 
1745              est_key = 'grid' 
1746              est_keys.append(est_key) 
1747              spin_id_list = [] 
1748   
1749              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1750                  # Add key to dic. 
1751                  my_dic[spin_id] = {} 
1752   
1753                  # Add key for estimate. 
1754                  my_dic[spin_id][est_key] = {} 
1755   
1756                  # Add spin key to list. 
1757                  spin_id_list.append(spin_id) 
1758   
1759                  # Generate spin string. 
1760                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1761   
1762                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1763                      # Generate the param_key. 
1764                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1765                      #param_key = generate_r20_key(exp_type=exp_type, frq=frq) 
1766   
1767                      # Append key. 
1768                      param_key_list.append(param_key) 
1769   
1770                      # Add key to dic. 
1771                      my_dic[spin_id][est_key][param_key] = {} 
1772   
1773                      # Get the value. 
1774                      # Loop over err attributes. 
1775                      for par_attr in par_attr_list: 
1776                          if hasattr(cur_spin, par_attr): 
1777                              get_par_attr = getattr(cur_spin, par_attr)[param_key] 
1778                          else: 
1779                              get_par_attr = 0.0 
1780   
1781                          # Save to dic. 
1782                          my_dic[spin_id][est_key][param_key][par_attr] = get_par_attr 
1783   
1784                      # Check number of values. 
1785                      values = [] 
1786                      errors = [] 
1787                      times = [] 
1788                      for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1789                          value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1790                          values.append(value) 
1791   
1792                          error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1793                          errors.append(error) 
1794                          times.append(time) 
1795   
1796                      # Save to dic. 
1797                      my_dic[spin_id][est_key][param_key]['values'] = values 
1798                      my_dic[spin_id][est_key][param_key]['errors'] = errors 
1799                      my_dic[spin_id][est_key][param_key]['times'] = times 
1800   
1801          # Analysis variables. 
1802          ##################### 
1803   
1804          # The dispersion models. 
1805          MODELS = ['R2eff', 'No Rex'] 
1806   
1807          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
1808          MC_NUM = 10 
1809   
1810          # A flag which if True will activate Monte Carlo simulations for all models.  Note this will hugely increase the computation time. 
1811          MC_SIM_ALL_MODELS = False 
1812   
1813          # The results directory. 
1814          RESULTS_DIR = ds.tmpdir 
1815   
1816          # The directory of results of an earlier analysis without clustering. 
1817          PRE_RUN_DIR = None 
1818   
1819          # The model selection technique to use. 
1820          MODSEL = 'AIC' 
1821   
1822          # The flag for only using numeric models in the final model selection. 
1823          NUMERIC_ONLY = False 
1824   
1825          # The R1rho value in rad/s by which to judge insignificance.  If the maximum difference between two points on all dispersion curves for a spin is less than this value, that spin will be deselected. 
1826          INSIGNIFICANCE = 1.0 
1827   
1828          # Auto-analysis execution. 
1829          self.assertRaises(RelaxError, relax_disp.Relax_disp, pipe_name='relax_disp', results_dir=RESULTS_DIR, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, insignificance=INSIGNIFICANCE, numeric_only=NUMERIC_ONLY) 
1830   
1831   
1832 -    def test_bug_negative_intensities_cpmg(self): 
1833          """Test data, where peak intensities are negative in CPMG 
1834   
1835          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
1836          """ 
1837   
1838          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'bug_neg_int_acbp_cpmg_disp_048MGuHCl_40C_041223' 
1839   
1840          # Create the spins 
1841          self.interpreter.spectrum.read_spins(file="peaks_list_max_standard.ser", dir=data_path) 
1842   
1843          # Name the isotope for field strength scaling. 
1844          self.interpreter.spin.isotope(isotope='15N') 
1845   
1846          # Read the spectrum from NMRSeriesTab file. The "auto" will generate spectrum name of form: Z_A{i} 
1847          self.interpreter.spectrum.read_intensities(file="peaks_list_max_standard.ser", dir=data_path, spectrum_id='auto', int_method='height') 
1848   
1849          # Loop over the spectra settings. 
1850          ncycfile=open(data_path + sep + 'ncyc.txt', 'r') 
1851   
1852          # Make empty ncyclist 
1853          ncyclist = [] 
1854   
1855          i = 0 
1856          for line in ncycfile: 
1857              ncyc = line.split()[0] 
1858              time_T2 = float(line.split()[1]) 
1859              vcpmg = line.split()[2] 
1860              set_sfrq = float(line.split()[3]) 
1861              rmsd_err = float(line.split()[4]) 
1862   
1863              # Test if spectrum is a reference 
1864              if float(vcpmg) == 0.0: 
1865                  vcpmg = None 
1866              else: 
1867                  vcpmg = round(float(vcpmg), 3) 
1868   
1869              # Add ncyc to list 
1870              ncyclist.append(int(ncyc)) 
1871   
1872              # Set the current spectrum id 
1873              current_id = "Z_A%s"%(i) 
1874   
1875              # Set the current experiment type. 
1876              self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
1877   
1878              # Set the peak intensity errors, as defined as the baseplane RMSD. 
1879              self.interpreter.spectrum.baseplane_rmsd(error=rmsd_err, spectrum_id=current_id) 
1880   
1881              # Set the NMR field strength of the spectrum. 
1882              self.interpreter.spectrometer.frequency(id=current_id, frq=set_sfrq, units='MHz') 
1883   
1884              # Relaxation dispersion CPMG constant time delay T (in s). 
1885              self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
1886   
1887              # Set the relaxation dispersion CPMG frequencies. 
1888              self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
1889   
1890              i += 1 
1891   
1892          # Specify the duplicated spectra. 
1893          self.interpreter.spectrum.replicated(spectrum_ids=['Z_A1', 'Z_A15']) 
1894   
1895          # Delete replicate spectrum 
1896          #self.interpreter.spectrum.delete('Z_A15') 
1897   
1898          MODELS = [MODEL_R2EFF, MODEL_NOREX] 
1899          GRID_INC = 5; MC_NUM = 3; MODSEL = 'AIC' 
1900   
1901          results_dir = ds.tmpdir 
1902   
1903          # Execute 
1904          relax_disp.Relax_disp(pipe_name='relax_disp', results_dir=results_dir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
1905   
1906          # Check spin less R2eff points. 
1907          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
1908              # Assert that spin 4, has one less R2eff point, since one of the intensities are negative. 
1909              if spin_id == ':4@N': 
1910                  self.assertEqual(len(cur_spin.r2eff), 14) 
1911              else: 
1912                  self.assertEqual(len(cur_spin.r2eff), 15) 
1913   
1914   
1915 -    def test_check_missing_r1(self): 
1916          """Test of the check_missing_r1() function.""" 
1917   
1918          # Set up some spins. 
1919          self.setup_missing_r1_spins() 
1920   
1921          # Set variables. 
1922          exp_type = 'R1rho' 
1923          frq = 800.1 * 1E6 
1924   
1925          spectrum_id='test' 
1926   
1927          # Set an experiment type to the pipe. 
1928          self.interpreter.relax_disp.exp_type(spectrum_id=spectrum_id, exp_type=exp_type) 
1929   
1930          # Set a frequency to loop through. 
1931          self.interpreter.spectrometer.frequency(id=spectrum_id, frq=frq, units='Hz') 
1932   
1933          # Check R1 for DPL94. 
1934          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
1935          self.assertEqual(check_missing_r1_return, True) 
1936   
1937          # Check R1 for R2eff. 
1938          check_missing_r1_return = check_missing_r1(model=MODEL_R2EFF) 
1939          self.assertEqual(check_missing_r1_return, False) 
1940   
1941          # The path to the data files. 
1942          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
1943   
1944          # Now load some R1 data. 
1945          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
1946   
1947          # Check R1. 
1948          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
1949          self.assertEqual(check_missing_r1_return, False) 
1950   
1951   
1952 -    def test_cpmg_synthetic_b14_to_ns3d_cluster(self): 
1953          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site 3D, for clustered analysis. 
1954   
1955          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
1956   
1957          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
1958          """ 
1959   
1960          # Reset. 
1961          #self.interpreter.reset() 
1962   
1963          ## Set Experiments. 
1964          model_create = 'B14' 
1965          #model_create = 'NS CPMG 2-site expanded' 
1966          model_analyse = 'NS CPMG 2-site 3D' 
1967   
1968          # Exp 1 
1969          sfrq_1 = 599.8908617*1E6 
1970          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
1971          time_T2_1 = 0.06 
1972          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
1973          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
1974          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
1975          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
1976   
1977          sfrq_2 = 499.8908617*1E6 
1978          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
1979          time_T2_2 = 0.05 
1980          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
1981          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
1982          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
1983          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
1984   
1985          # Collect all exps 
1986          exps = [exp_1, exp_2] 
1987   
1988          spins = [ 
1989              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
1990              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
1991              ] 
1992   
1993          # Collect the data to be used. 
1994          ds.data = [model_create, model_analyse, spins, exps] 
1995   
1996          # The tmp directory. None is the local directory. 
1997          ds.tmpdir = ds.tmpdir 
1998   
1999          # The results directory. None is the local directory. 
2000          #ds.resdir = None 
2001          ds.resdir = ds.tmpdir 
2002   
2003          # Do r20_from_min_r2eff ?. 
2004          ds.r20_from_min_r2eff = True 
2005   
2006          # Remove insignificant level. 
2007          ds.insignificance = 0.0 
2008   
2009          # The grid search size (the number of increments per dimension). 
2010          ds.GRID_INC = None 
2011   
2012          # The do clustering. 
2013          ds.do_cluster = True 
2014   
2015          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2016          # The default value is 1e-25. 
2017          ds.set_func_tol = 1e-1 
2018   
2019          # The maximum number of iterations. 
2020          # The default value is 1e7. 
2021          ds.set_max_iter = 1000 
2022   
2023          # The verbosity level. 
2024          ds.verbosity = 1 
2025   
2026          # The rel_change WARNING level. 
2027          ds.rel_change = 0.05 
2028   
2029          # The plot_curves. 
2030          ds.plot_curves = False 
2031   
2032          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2033          ds.sherekhan_input = False 
2034   
2035          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2036          ds.opendx = False 
2037   
2038          # The set r2eff err. 
2039          ds.r2eff_err = 0.1 
2040   
2041          # The print result info. 
2042          ds.print_res = True 
2043   
2044          # Execute the script. 
2045          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2046   
2047          cur_spins = ds.data[2] 
2048          # Compare results. 
2049          for i in range(len(cur_spins)): 
2050              res_name, res_num, spin_name, params = cur_spins[i] 
2051              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2052              cur_spin = return_spin(cur_spin_id) 
2053   
2054              grid_params = ds.grid_results[i][3] 
2055   
2056              # Extract the clust results. 
2057              min_params = ds.clust_results[i][3] 
2058              # Now read the parameters. 
2059              print("For spin: '%s'"%cur_spin_id) 
2060              for mo_param in cur_spin.params: 
2061                  # The R2 is a dictionary, depending on spectrometer frequency. 
2062                  if isinstance(getattr(cur_spin, mo_param), dict): 
2063                      grid_r2 = grid_params[mo_param] 
2064                      min_r2 = min_params[mo_param] 
2065                      set_r2 = params[mo_param] 
2066                      for key, val in list(set_r2.items()): 
2067                          grid_r2_frq = grid_r2[key] 
2068                          min_r2_frq = min_r2[key] 
2069                          set_r2_frq = set_r2[key] 
2070                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2071                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2072                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2073                          if rel_change > ds.rel_change: 
2074                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2075                              print("###################################") 
2076   
2077                          ## Make test on R2. 
2078                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2079                  else: 
2080                      grid_val = grid_params[mo_param] 
2081                      min_val = min_params[mo_param] 
2082                      set_val = params[mo_param] 
2083                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2084                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2085                      if rel_change > ds.rel_change: 
2086                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2087                          print("###################################") 
2088   
2089                      ## Make test on parameters. 
2090                      if mo_param == 'dw': 
2091                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2092                      elif mo_param == 'kex': 
2093                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2094                      elif mo_param == 'pA': 
2095                          self.assertAlmostEqual(set_val, min_val, 2) 
2096   
2097   
2098 -    def test_cpmg_synthetic_b14_to_ns_star_cluster(self): 
2099          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site STAR, for clustered analysis. 
2100   
2101          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2102   
2103          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2104          """ 
2105   
2106          # Reset. 
2107          #self.interpreter.reset() 
2108   
2109          ## Set Experiments. 
2110          model_create = 'B14' 
2111          #model_create = 'NS CPMG 2-site expanded' 
2112          model_analyse = 'NS CPMG 2-site star' 
2113   
2114          # Exp 1 
2115          sfrq_1 = 599.8908617*1E6 
2116          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2117          time_T2_1 = 0.06 
2118          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2119          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2120          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2121          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2122   
2123          sfrq_2 = 499.8908617*1E6 
2124          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2125          time_T2_2 = 0.05 
2126          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2127          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2128          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2129          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2130   
2131          # Collect all exps 
2132          exps = [exp_1, exp_2] 
2133   
2134          spins = [ 
2135              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2136              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2137              ] 
2138   
2139          # Collect the data to be used. 
2140          ds.data = [model_create, model_analyse, spins, exps] 
2141   
2142          # The tmp directory. None is the local directory. 
2143          ds.tmpdir = ds.tmpdir 
2144   
2145          # The results directory. None is the local directory. 
2146          #ds.resdir = None 
2147          ds.resdir = ds.tmpdir 
2148   
2149          # Do r20_from_min_r2eff ?. 
2150          ds.r20_from_min_r2eff = True 
2151   
2152          # Remove insignificant level. 
2153          ds.insignificance = 0.0 
2154   
2155          # The grid search size (the number of increments per dimension). 
2156          ds.GRID_INC = None 
2157   
2158          # The do clustering. 
2159          ds.do_cluster = True 
2160   
2161          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2162          # The default value is 1e-25. 
2163          ds.set_func_tol = 1e-1 
2164   
2165          # The maximum number of iterations. 
2166          # The default value is 1e7. 
2167          ds.set_max_iter = 1000 
2168   
2169          # The verbosity level. 
2170          ds.verbosity = 1 
2171   
2172          # The rel_change WARNING level. 
2173          ds.rel_change = 0.05 
2174   
2175          # The plot_curves. 
2176          ds.plot_curves = False 
2177   
2178          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2179          ds.sherekhan_input = False 
2180   
2181          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2182          ds.opendx = False 
2183   
2184          # The set r2eff err. 
2185          ds.r2eff_err = 0.1 
2186   
2187          # The print result info. 
2188          ds.print_res = True 
2189   
2190          # Execute the script. 
2191          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2192   
2193          cur_spins = ds.data[2] 
2194          # Compare results. 
2195          for i in range(len(cur_spins)): 
2196              res_name, res_num, spin_name, params = cur_spins[i] 
2197              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2198              cur_spin = return_spin(cur_spin_id) 
2199   
2200              grid_params = ds.grid_results[i][3] 
2201   
2202              # Extract the clust results. 
2203              min_params = ds.clust_results[i][3] 
2204              # Now read the parameters. 
2205              print("For spin: '%s'"%cur_spin_id) 
2206              for mo_param in cur_spin.params: 
2207                  # The R2 is a dictionary, depending on spectrometer frequency. 
2208                  if isinstance(getattr(cur_spin, mo_param), dict): 
2209                      grid_r2 = grid_params[mo_param] 
2210                      min_r2 = min_params[mo_param] 
2211                      set_r2 = params[mo_param] 
2212                      for key, val in list(set_r2.items()): 
2213                          grid_r2_frq = grid_r2[key] 
2214                          min_r2_frq = min_r2[key] 
2215                          set_r2_frq = set_r2[key] 
2216                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2217                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2218                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2219                          if rel_change > ds.rel_change: 
2220                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2221                              print("###################################") 
2222   
2223                          ## Make test on R2. 
2224                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2225                  else: 
2226                      grid_val = grid_params[mo_param] 
2227                      min_val = min_params[mo_param] 
2228                      set_val = params[mo_param] 
2229                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2230                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2231                      if rel_change > ds.rel_change: 
2232                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2233                          print("###################################") 
2234   
2235                      ## Make test on parameters. 
2236                      if mo_param == 'dw': 
2237                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2238                      elif mo_param == 'kex': 
2239                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2240                      elif mo_param == 'pA': 
2241                          self.assertAlmostEqual(set_val, min_val, 2) 
2242   
2243   
2244 -    def test_cpmg_synthetic_ns3d_to_cr72(self): 
2245          """Test synthetic cpmg data. 
2246   
2247          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with CR72. 
2248          """ 
2249   
2250          # Reset. 
2251          #self.interpreter.reset() 
2252   
2253          ## Set Experiments. 
2254          model_create = 'NS CPMG 2-site 3D' 
2255          #model_create = 'NS CPMG 2-site expanded' 
2256          model_analyse = 'CR72' 
2257          # Exp 1 
2258          sfrq_1 = 599.8908617*1E6 
2259          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2260          time_T2_1 = 0.06 
2261          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2262          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2263          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2264   
2265          sfrq_2 = 499.8908617*1E6 
2266          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2267          time_T2_2 = 0.05 
2268          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2269          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2270          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2271   
2272          # Collect all exps 
2273          exps = [exp_1, exp_2] 
2274   
2275          spins = [ 
2276              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2277              ] 
2278   
2279          # Collect the data to be used. 
2280          ds.data = [model_create, model_analyse, spins, exps] 
2281   
2282          # The tmp directory. None is the local directory. 
2283          ds.tmpdir = ds.tmpdir 
2284   
2285          # The results directory. None is the local directory. 
2286          #ds.resdir = None 
2287          ds.resdir = ds.tmpdir 
2288   
2289          # Do r20_from_min_r2eff ?. 
2290          ds.r20_from_min_r2eff = True 
2291   
2292          # Remove insignificant level. 
2293          ds.insignificance = 0.0 
2294   
2295          # The grid search size (the number of increments per dimension). 
2296          ds.GRID_INC = 8 
2297   
2298          # The do clustering. 
2299          ds.do_cluster = False 
2300   
2301          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2302          # The default value is 1e-25. 
2303          ds.set_func_tol = 1e-9 
2304   
2305          # The maximum number of iterations. 
2306          # The default value is 1e7. 
2307          ds.set_max_iter = 1000 
2308   
2309          # The verbosity level. 
2310          ds.verbosity = 1 
2311   
2312          # The rel_change WARNING level. 
2313          ds.rel_change = 0.05 
2314   
2315          # The plot_curves. 
2316          ds.plot_curves = False 
2317   
2318          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2319          ds.sherekhan_input = False 
2320   
2321          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2322          ds.opendx = False 
2323   
2324          # The set r2eff err. 
2325          ds.r2eff_err = 0.1 
2326   
2327          # The print result info. 
2328          ds.print_res = False 
2329   
2330          # Execute the script. 
2331          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2332   
2333          cur_spins = ds.data[2] 
2334          # Compare results. 
2335          for i in range(len(cur_spins)): 
2336              res_name, res_num, spin_name, params = cur_spins[i] 
2337              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2338              cur_spin = return_spin(cur_spin_id) 
2339   
2340              grid_params = ds.grid_results[i][3] 
2341              min_params = ds.min_results[i][3] 
2342              # Now read the parameters. 
2343              print("For spin: '%s'"%cur_spin_id) 
2344              for mo_param in cur_spin.params: 
2345                  # The R2 is a dictionary, depending on spectrometer frequency. 
2346                  if isinstance(getattr(cur_spin, mo_param), dict): 
2347                      grid_r2 = grid_params[mo_param] 
2348                      min_r2 = min_params[mo_param] 
2349                      set_r2 = params[mo_param] 
2350                      for key, val in list(set_r2.items()): 
2351                          grid_r2_frq = grid_r2[key] 
2352                          min_r2_frq = min_r2[key] 
2353                          set_r2_frq = set_r2[key] 
2354                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2355                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2356                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2357                          if rel_change > ds.rel_change: 
2358                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2359                              print("###################################") 
2360   
2361                          ## Make test on R2. 
2362                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2363                  else: 
2364                      grid_val = grid_params[mo_param] 
2365                      min_val = min_params[mo_param] 
2366                      set_val = params[mo_param] 
2367                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2368                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2369                      if rel_change > ds.rel_change: 
2370                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2371                          print("###################################") 
2372   
2373                      ## Make test on parameters. 
2374                      if mo_param == 'dw': 
2375                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2376                      elif mo_param == 'kex': 
2377                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2378                      elif mo_param == 'pA': 
2379                          self.assertAlmostEqual(set_val, min_val, 3) 
2380   
2381   
2382 -    def test_cpmg_synthetic_ns3d_to_b14(self): 
2383          """Test synthetic cpmg data. 
2384   
2385          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with B14. 
2386          Try to catch bug #22021 U{https://gna.org/bugs/index.php?22021}: Model B14 shows bad fitting to data. 
2387          """ 
2388   
2389          # Reset. 
2390          #self.interpreter.reset() 
2391   
2392          ## Set Experiments. 
2393          model_create = 'NS CPMG 2-site 3D' 
2394          #model_create = 'NS CPMG 2-site expanded' 
2395          model_analyse = 'B14' 
2396          # Exp 1 
2397          sfrq_1 = 599.8908617*1E6 
2398          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2399          time_T2_1 = 0.06 
2400          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2401          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2402          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2403   
2404          sfrq_2 = 499.8908617*1E6 
2405          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2406          time_T2_2 = 0.05 
2407          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2408          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2409          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2410   
2411          # Collect all exps 
2412          exps = [exp_1, exp_2] 
2413   
2414          spins = [ 
2415              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2416              ] 
2417   
2418          # Collect the data to be used. 
2419          ds.data = [model_create, model_analyse, spins, exps] 
2420   
2421          # The tmp directory. None is the local directory. 
2422          ds.tmpdir = ds.tmpdir 
2423   
2424          # The results directory. None is the local directory. 
2425          #ds.resdir = None 
2426          ds.resdir = ds.tmpdir 
2427   
2428          # Do r20_from_min_r2eff ?. 
2429          ds.r20_from_min_r2eff = True 
2430   
2431          # Remove insignificant level. 
2432          ds.insignificance = 0.0 
2433   
2434          # The grid search size (the number of increments per dimension). 
2435          ds.GRID_INC = 8 
2436   
2437          # The do clustering. 
2438          ds.do_cluster = False 
2439   
2440          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2441          # The default value is 1e-25. 
2442          ds.set_func_tol = 1e-9 
2443   
2444          # The maximum number of iterations. 
2445          # The default value is 1e7. 
2446          ds.set_max_iter = 1000 
2447   
2448          # The verbosity level. 
2449          ds.verbosity = 1 
2450   
2451          # The rel_change WARNING level. 
2452          ds.rel_change = 0.05 
2453   
2454          # The plot_curves. 
2455          ds.plot_curves = False 
2456   
2457          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2458          ds.sherekhan_input = False 
2459   
2460          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2461          ds.opendx = False 
2462   
2463          # The set r2eff err. 
2464          ds.r2eff_err = 0.1 
2465   
2466          # The print result info. 
2467          ds.print_res = False 
2468   
2469          # Execute the script. 
2470          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2471   
2472          cur_spins = ds.data[2] 
2473          # Compare results. 
2474          for i in range(len(cur_spins)): 
2475              res_name, res_num, spin_name, params = cur_spins[i] 
2476              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2477              cur_spin = return_spin(cur_spin_id) 
2478   
2479              grid_params = ds.grid_results[i][3] 
2480              min_params = ds.min_results[i][3] 
2481              # Now read the parameters. 
2482              print("For spin: '%s'"%cur_spin_id) 
2483              for mo_param in cur_spin.params: 
2484                  # The R2 is a dictionary, depending on spectrometer frequency. 
2485                  if isinstance(getattr(cur_spin, mo_param), dict): 
2486                      grid_r2 = grid_params[mo_param] 
2487                      min_r2 = min_params[mo_param] 
2488                      set_r2 = params[mo_param] 
2489                      for key, val in list(set_r2.items()): 
2490                          grid_r2_frq = grid_r2[key] 
2491                          min_r2_frq = min_r2[key] 
2492                          set_r2_frq = set_r2[key] 
2493                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2494                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2495                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2496                          if rel_change > ds.rel_change: 
2497                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2498                              print("###################################") 
2499   
2500                          ## Make test on R2. 
2501                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2502                  else: 
2503                      grid_val = grid_params[mo_param] 
2504                      min_val = min_params[mo_param] 
2505                      set_val = params[mo_param] 
2506                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2507                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2508                      if rel_change > ds.rel_change: 
2509                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2510                          print("###################################") 
2511   
2512                      ## Make test on parameters. 
2513                      if mo_param == 'dw': 
2514                          self.assertAlmostEqual(set_val/10, min_val/10, 5) 
2515                      elif mo_param == 'kex': 
2516                          self.assertAlmostEqual(set_val/1000, min_val/1000, 5) 
2517                      elif mo_param == 'pA': 
2518                          self.assertAlmostEqual(set_val, min_val, 6) 
2519   
2520   
2521 -    def test_cpmg_synthetic_ns3d_to_cr72_noise_cluster(self): 
2522          """Test synthetic cpmg data. For CR72 with small noise and cluster. 
2523   
2524          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2525          """ 
2526   
2527          # Reset. 
2528          #self.interpreter.reset() 
2529   
2530          ## Set Experiments. 
2531          model_create = 'NS CPMG 2-site 3D' 
2532          #model_create = 'NS CPMG 2-site expanded' 
2533          model_analyse = 'CR72' 
2534   
2535          # Exp 1 
2536          sfrq_1 = 599.8908617*1E6 
2537          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2538          time_T2_1 = 0.06 
2539          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2540          r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2541          #r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2542          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2543   
2544          sfrq_2 = 499.8908617*1E6 
2545          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2546          time_T2_2 = 0.05 
2547          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2548          r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2549          #r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2550          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2551   
2552          # Collect all exps 
2553          exps = [exp_1, exp_2] 
2554   
2555          spins = [ 
2556              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ], 
2557              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.99, 'dw': 1.} ] 
2558              ] 
2559   
2560          # Collect the data to be used. 
2561          ds.data = [model_create, model_analyse, spins, exps] 
2562   
2563          # The tmp directory. None is the local directory. 
2564          ds.tmpdir = ds.tmpdir 
2565   
2566          # The results directory. None is the local directory. 
2567          #ds.resdir = None 
2568          ds.resdir = ds.tmpdir 
2569   
2570          # Do r20_from_min_r2eff ?. 
2571          ds.r20_from_min_r2eff = True 
2572   
2573          # Remove insignificant level. 
2574          ds.insignificance = 0.0 
2575   
2576          # The grid search size (the number of increments per dimension). 
2577          ds.GRID_INC = 13 
2578   
2579          # The do clustering. 
2580          ds.do_cluster = True 
2581   
2582          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2583          # The default value is 1e-25. 
2584          ds.set_func_tol = 1e-8 
2585   
2586          # The maximum number of iterations. 
2587          # The default value is 1e7. 
2588          ds.set_max_iter = 10000 
2589   
2590          # The verbosity level. 
2591          ds.verbosity = 1 
2592   
2593          # The rel_change WARNING level. 
2594          ds.rel_change = 0.05 
2595   
2596          # The plot_curves. 
2597          ds.plot_curves = False 
2598   
2599          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2600          ds.sherekhan_input = False 
2601   
2602          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2603          ds.opendx = False 
2604   
2605          # The set r2eff err. 
2606          ds.r2eff_err = 0.1 
2607   
2608          # The print result info. 
2609          ds.print_res = False 
2610   
2611          # Execute the script. 
2612          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2613   
2614          cur_spins = ds.data[2] 
2615          # Compare results. 
2616          for i in range(len(cur_spins)): 
2617              res_name, res_num, spin_name, params = cur_spins[i] 
2618              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2619              cur_spin = return_spin(cur_spin_id) 
2620   
2621              grid_params = ds.grid_results[i][3] 
2622   
2623              # Extract the clust results. 
2624              min_params = ds.clust_results[i][3] 
2625              # Now read the parameters. 
2626              print("For spin: '%s'"%cur_spin_id) 
2627              for mo_param in cur_spin.params: 
2628                  # The R2 is a dictionary, depending on spectrometer frequency. 
2629                  if isinstance(getattr(cur_spin, mo_param), dict): 
2630                      grid_r2 = grid_params[mo_param] 
2631                      min_r2 = min_params[mo_param] 
2632                      set_r2 = params[mo_param] 
2633                      for key, val in list(set_r2.items()): 
2634                          grid_r2_frq = grid_r2[key] 
2635                          min_r2_frq = min_r2[key] 
2636                          set_r2_frq = set_r2[key] 
2637                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2638                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2639                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2640                          if rel_change > ds.rel_change: 
2641                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2642                              print("###################################") 
2643   
2644                          ## Make test on R2. 
2645                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2646                  else: 
2647                      grid_val = grid_params[mo_param] 
2648                      min_val = min_params[mo_param] 
2649                      set_val = params[mo_param] 
2650                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2651                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2652                      if rel_change > ds.rel_change: 
2653                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2654                          print("###################################") 
2655   
2656                      ## Make test on parameters. 
2657                      if mo_param == 'dw': 
2658                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2659                      elif mo_param == 'kex': 
2660                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2661                      elif mo_param == 'pA': 
2662                          self.assertAlmostEqual(set_val, min_val, 2) 
2663   
2664   
2665 -    def test_cpmg_synthetic_dx_map_points(self): 
2666          """Test synthetic cpmg data, calling the dx.map function with one or two points. 
2667   
2668          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2669          """ 
2670   
2671          # Reset. 
2672          #self.interpreter.reset() 
2673   
2674          ## Set Experiments. 
2675          model_create = MODEL_NS_CPMG_2SITE_EXPANDED 
2676          model_analyse = 'CR72' 
2677          # Exp 1 
2678          sfrq_1 = 599.8908617*1E6 
2679          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2680          time_T2_1 = 0.06 
2681          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2682          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2683          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2684   
2685          sfrq_2 = 499.8908617*1E6 
2686          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2687          time_T2_2 = 0.05 
2688          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2689          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2690          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2691   
2692          # Collect all exps 
2693          exps = [exp_1, exp_2] 
2694   
2695          spins = [ 
2696              ['Ala', 1, 'N', {'r2': {r20_key_1:2, r20_key_2:2}, 'r2a': {r20_key_1:2, r20_key_2:2}, 'r2b': {r20_key_1:2, r20_key_2:2}, 'kex': 1000, 'pA': 0.99, 'dw': 2} ] 
2697              ] 
2698   
2699          # Collect the data to be used. 
2700          ds.data = [model_create, model_analyse, spins, exps] 
2701   
2702          # The tmp directory. None is the local directory. 
2703          ds.tmpdir = ds.tmpdir 
2704   
2705          # The results directory. None is the local directory. 
2706          #ds.resdir = None 
2707          ds.resdir = ds.tmpdir 
2708   
2709          # Do r20_from_min_r2eff ?. 
2710          ds.r20_from_min_r2eff = True 
2711   
2712          # Remove insignificant level. 
2713          ds.insignificance = 0.0 
2714   
2715          # The grid search size (the number of increments per dimension). 
2716          ds.GRID_INC = None 
2717   
2718          # The do clustering. 
2719          ds.do_cluster = False 
2720   
2721          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2722          # The default value is 1e-25. 
2723          ds.set_func_tol = 1e-9 
2724   
2725          # The maximum number of iterations. 
2726          # The default value is 1e7. 
2727          ds.set_max_iter = 1000 
2728   
2729          # The verbosity level. 
2730          ds.verbosity = 1 
2731   
2732          # The rel_change WARNING level. 
2733          ds.rel_change = 0.05 
2734   
2735          # The plot_curves. 
2736          ds.plot_curves = False 
2737   
2738          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2739          ds.sherekhan_input = False 
2740   
2741          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2742          ds.opendx = False 
2743   
2744          # The set r2eff err. 
2745          ds.r2eff_err = 0.1 
2746   
2747          # The print result info. 
2748          ds.print_res = False 
2749   
2750          # Execute the script. 
2751          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2752   
2753          # Get the spins. 
2754          cur_spins = ds.data[2] 
2755   
2756          # First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-) 
2757          ds.pipe_name_MODEL_MAP = "%s_%s_map"%(ds.pipe_name, model_analyse) 
2758          self.interpreter.pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL_MAP, bundle_to = ds.pipe_bundle) 
2759          self.interpreter.pipe.switch(pipe_name=ds.pipe_name_MODEL_MAP) 
2760   
2761          # Copy R2eff, but not the original parameters 
2762          self.interpreter.value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_MAP, param='r2eff') 
2763   
2764          # Then select model. 
2765          self.interpreter.relax_disp.select_model(model=model_analyse) 
2766   
2767          # Define dx.map settings. 
2768          ds.dx_inc = 4 
2769          ds.dx_params = ['dw', 'pA', 'kex'] 
2770   
2771          res_name, res_num, spin_name, params = cur_spins[0] 
2772          cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2773          cur_spin = return_spin(cur_spin_id) 
2774   
2775          print("Params for dx map is") 
2776          print(ds.dx_params) 
2777          print("Point param for dx map is") 
2778          print(ds.dx_set_val) 
2779          cur_model = model_analyse.replace(' ', '_') 
2780          file_name_map = "%s_map%s" % (cur_model, cur_spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
2781          file_name_point = "%s_point%s" % (cur_model, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
2782          self.interpreter.dx.map(params=ds.dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=10, file_prefix=file_name_map, dir=ds.resdir, point=[ds.dx_set_val, ds.dx_clust_val], point_file=file_name_point, create_par_file=True) 
2783   
2784          ## Check for file creation 
2785          # Set filepaths. 
2786          map_cfg = ds.tmpdir+sep+file_name_map+".cfg" 
2787          map_net = ds.tmpdir+sep+file_name_map+".net" 
2788          map_general = ds.tmpdir+sep+file_name_map+".general" 
2789          map_par = get_file_path(file_name=file_name_map+".par", dir=ds.tmpdir) 
2790          map_plot = get_file_path(file_name=file_name_map+".py", dir=ds.tmpdir) 
2791   
2792          point_general = ds.tmpdir+sep+file_name_point+".general" 
2793          point_point = ds.tmpdir+sep+file_name_point 
2794          point_par = get_file_path(file_name=file_name_point+".par", dir=ds.tmpdir) 
2795   
2796          # Test the files exists. 
2797          self.assert_(access(map_cfg, F_OK)) 
2798          self.assert_(access(map_net, F_OK)) 
2799          self.assert_(access(map_general, F_OK)) 
2800          self.assert_(access(map_par, F_OK)) 
2801          self.assert_(access(map_plot, F_OK)) 
2802          self.assert_(access(point_general, F_OK)) 
2803          self.assert_(access(point_point, F_OK)) 
2804          self.assert_(access(point_par, F_OK)) 
2805   
2806          # Open the files for testing. 
2807          # Check the cfg file. 
2808          print("\nChecking the dx map .cfg file.") 
2809          res_file = [ 
2810              '//'+"\n", 
2811              '//'+"\n", 
2812              '// time: Thu May  8 18:55:31 2014'+"\n", 
2813              '//'+"\n", 
2814              '// version: 3.2.0 (format), 4.3.2 (DX)'+"\n", 
2815              '//'+"\n", 
2816              '//'+"\n", 
2817              '// panel[0]: position = (0.0164,0.0000), size = 0.2521x0.1933, startup = 1, devstyle = 1'+"\n", 
2818              '// title: value = Control Panel'+"\n", 
2819              '//'+"\n", 
2820              '// workspace: width = 251, height = 142'+"\n", 
2821              '// layout: snap = 0, width = 50, height = 50, align = NN'+"\n", 
2822              '//'+"\n", 
2823              '// interactor Selector[1]: num_components = 1, value = 1 '+"\n", 
2824              '// selections: maximum = 2, current = 0 '+"\n", 
2825              '// option[0]: name = "Colour", value = 1'+"\n", 
2826              '// option[1]: name = "Grey", value = 2'+"\n", 
2827              '// instance: panel = 0, x = 81, y = 6, style = Scrolled List, vertical = 1, size = 170x136'+"\n", 
2828              '// label: value = Colour Selector'+"\n", 
2829              '//'+"\n", 
2830              '// node Image[3]:'+"\n", 
2831              '// title: value = Surface'+"\n", 
2832              '// depth: value = 24'+"\n", 
2833              '// window: position = (0.0000,0.0400), size = 0.9929x0.9276'+"\n", 
2834          ] 
2835          file = open(map_cfg, 'r') 
2836          lines = file.readlines() 
2837          file.close() 
2838          for i in range(len(res_file)): 
2839              # Skip time point 
2840              if i == 2: 
2841                  continue 
2842              self.assertEqual(res_file[i], lines[i]) 
2843   
2844          print("\nChecking the dx map .general file.") 
2845          res_file = [ 
2846              'file = CR72_map_1_N'+"\n", 
2847              'grid = 5 x 5 x 5'+"\n", 
2848              'format = ascii'+"\n", 
2849              'interleaving = field'+"\n", 
2850              'majority = row'+"\n", 
2851              'field = data'+"\n", 
2852              'structure = scalar'+"\n", 
2853              'type = float'+"\n", 
2854              'dependency = positions'+"\n", 
2855              'positions = regular, regular, regular, 0, 1, 0, 1, 0, 1'+"\n", 
2856              ''+"\n", 
2857              'end'+"\n", 
2858          ] 
2859          file = open(map_general, 'r') 
2860          lines = file.readlines() 
2861          file.close() 
2862          for i in range(len(res_file)): 
2863              # Skip time point 
2864              #if i == 2: 
2865              #    continue 
2866              self.assertEqual(res_file[i], lines[i]) 
2867   
2868          print("\nChecking the dx point .general file.") 
2869          res_file = [ 
2870              'file = CR72_point_1_N'+"\n", 
2871              'points = 2'+"\n", 
2872              'format = ascii'+"\n", 
2873              'interleaving = field'+"\n", 
2874              'field = locations, field0'+"\n", 
2875              'structure = 3-vector, scalar'+"\n", 
2876              'type = float, float'+"\n", 
2877              ''+"\n", 
2878              'end'+"\n", 
2879          ] 
2880          file = open(point_general, 'r') 
2881          lines = file.readlines() 
2882          file.close() 
2883          for i in range(len(res_file)): 
2884              # Skip time point 
2885              #if i == 2: 
2886              #    continue 
2887              self.assertEqual(res_file[i], lines[i]) 
2888   
2889          print("\nChecking the dx point point file.") 
2890          res_file = [ 
2891              '0.8            3.92           0.39964        1'+"\n", 
2892              '0.76981        3.9169         0.41353        1'+"\n", 
2893          ] 
2894          file = open(point_point, 'r') 
2895          lines = file.readlines() 
2896          file.close() 
2897          for i in range(len(res_file)): 
2898              # Skip time point 
2899              #if i == 2: 
2900              #    continue 
2901              self.assertEqual(res_file[i], lines[i]) 
2902   
2903          print("\nChecking the dx point par file.") 
2904          res_file = [ 
2905              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
2906              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
2907              '1      1.92453    0.98961    1034.72206    6396.02770    1         1.92453    0.98961    1034.72206    6396.02770    '+"\n", 
2908          ] 
2909          res_file2 = [ 
2910              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
2911              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
2912              '1      1.92452    0.98961    1034.72424    6396.02439    1         1.92452    0.98961    1034.72424    6396.02439    '+"\n", 
2913          ]  # Python 2.5 and 3.1. 
2914          file = open(point_par, 'r') 
2915          lines = file.readlines() 
2916          file.close() 
2917          for i in range(len(res_file)): 
2918              if lines[i] != res_file[i] and lines[i] != res_file2[i]: 
2919                  self.assertEqual(res_file[i], lines[i]) 
2920   
2921          print("\nChecking the matplotlib surface plot file.") 
2922          res_file = [ 
2923              'from copy import deepcopy'+"\n", 
2924              'import numpy as np'+"\n", 
2925              'import scipy.interpolate'+"\n", 
2926              'from numpy.ma import masked_where'+"\n", 
2927              ''+"\n", 
2928              'from mpl_toolkits.mplot3d import axes3d'+"\n", 
2929              'import matplotlib.pyplot as plt'+"\n", 
2930              'from matplotlib import cm'+"\n", 
2931              ''+"\n", 
2932              '# Open file and get header.'+"\n", 
2933              'mapfile_name = "%s.par"'%file_name_map+"\n", 
2934              'pointfile_name = "%s.par"'%file_name_point+"\n", 
2935              ''+"\n", 
2936          ] 
2937          file = open(map_plot, 'r') 
2938          lines = file.readlines() 
2939          file.close() 
2940          for i in range(len(res_file)): 
2941              self.assertEqual(res_file[i], lines[i]) 
2942   
2943   
2944 -    def test_curve_type_cpmg_fixed_time(self): 
2945          """Test the curve type detection using the Dr. Flemming Hansen's CPMG fixed time test data.""" 
2946   
2947          # Reset. 
2948          self.interpreter.reset() 
2949   
2950          # Load the base data. 
2951          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
2952          self.interpreter.state.load(data_path+sep+'r2eff_values') 
2953   
2954          # The type. 
2955          curve_type = get_curve_type(id='500_133.33.in') 
2956          self.assertEqual(curve_type, 'fixed time') 
2957   
2958   
2959 -    def test_curve_type_r1rho_exponential(self, model=None): 
2960          """Test the curve type detection using the 'M61' exponential test data.""" 
2961   
2962          # Reset. 
2963          self.interpreter.reset() 
2964   
2965          # Load the base data. 
2966          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_on_res_m61' 
2967          self.interpreter.state.load(data_path+sep+'r2eff_values') 
2968   
2969          # The type. 
2970          curve_type = get_curve_type(id='nu_2000_ncyc9') 
2971          self.assertEqual(curve_type, 'exponential') 
2972   
2973   
2974 -    def test_curve_type_r1rho_fixed_time(self, model=None): 
2975          """Test the curve type detection using the 'TP02' fixed time test data.""" 
2976   
2977          # Reset. 
2978          self.interpreter.reset() 
2979   
2980          # Load the base data. 
2981          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
2982          self.interpreter.state.load(data_path+sep+'r2eff_values') 
2983   
2984          # The type. 
2985          curve_type = get_curve_type(id='nu_1000.0_500MHz') 
2986          self.assertEqual(curve_type, 'fixed time') 
2987   
2988   
2989 -    def test_dpl94_data_to_dpl94(self): 
2990          """Test the relaxation dispersion 'DPL94' model curve fitting to fixed time synthetic data.""" 
2991   
2992          # Fixed time variable. 
2993          ds.fixed = True 
2994   
2995          # Execute the script. 
2996          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_dpl94.py') 
2997   
2998          # The original parameters. 
2999          i0 = [100000.0, 20000.0] 
3000          r1rho_prime = [2.25, 24.0] 
3001          pA = 0.7 
3002          kex = 1000.0 
3003          delta_omega = [1.0, 2.0] 
3004          phi_ex = [] 
3005          for i in range(2): 
3006              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
3007   
3008          # Switch to the 'DPL94' model data pipe, then check for each spin. 
3009          self.interpreter.pipe.switch('DPL94 - relax_disp') 
3010          spin_index = 0 
3011          for spin, spin_id in spin_loop(return_id=True): 
3012              # Printout. 
3013              print("\nSpin %s." % spin_id) 
3014   
3015              # Check the fitted parameters. 
3016              self.assertAlmostEqual(spin.r2['R1rho - 800.00000000 MHz']/10, r1rho_prime[spin_index]/10, 2) 
3017              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
3018              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
3019   
3020              # Increment the spin index. 
3021              spin_index += 1 
3022   
3023   
3024 -    def test_dx_map_clustered(self): 
3025          """Test making dx_map for residues under clustered calculation. 
3026   
3027          This uses CPMG data from: 
3028              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE 
3029                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
3030                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, U{DOI 10.1002/prot.22886<http://dx.doi.org/10.1002/prot.22886>} 
3031          """ 
3032   
3033          # Define path to data  
3034          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
3035   
3036          # Read data. 
3037          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
3038   
3039          # Get residue of interest. 
3040          cur_spin_id = ":%i@%s"%(52, 'N') 
3041          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3042   
3043          # Get the spin container. 
3044          cur_spin = return_spin(cur_spin_id) 
3045   
3046          # Get the chi2 value 
3047          pre_chi2 = cur_spin.chi2 
3048   
3049          # Then do a local minimisation. 
3050          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3051          self.interpreter.minimise.calculate() 
3052   
3053          # Get the chi2 value after calculation. 
3054          calc_chi2 = cur_spin.chi2 
3055   
3056          # Assert calculation is equal. 
3057          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3058   
3059          # Define dx.map settings. 
3060          dx_inc = 2 
3061          dx_inc_sides = dx_inc / 2 
3062   
3063          dx_params = ['dw', 'pA', 'kex'] 
3064          dx_point_clustered_min = [cur_spin.dw, cur_spin.pA, cur_spin.kex] 
3065   
3066          print("Params for dx map is") 
3067          print(dx_params) 
3068          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3069          print(dx_point_clustered_min) 
3070   
3071          # Define file_names. 
3072          cur_model = 'CR72' 
3073          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3074          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3075   
3076          # Step-size of parameter is 10 % 
3077          param_delta = 0.1 
3078   
3079          # Determine bounds for lower and upper 
3080          lower = [] 
3081          upper = [] 
3082          for i, param_val in enumerate(dx_point_clustered_min): 
3083              param = dx_params[i] 
3084              step_val = param_delta * param_val 
3085              step_length = step_val * dx_inc_sides 
3086   
3087              # Calculate value 
3088              low_val = param_val - step_length 
3089              lower.append(low_val) 
3090   
3091              upp_val = param_val + step_length 
3092              upper.append(upp_val) 
3093   
3094              print("For param %s, lower=%3.3f, upper=%3.3f, step_value=%3.3f, steps=%i, centered at=%3.3f"% (param, low_val, upp_val, step_val, dx_inc, param_val)) 
3095   
3096          # If the number of increments are 2, there will be 3 point calculations per parameter. 
3097          # Since we have ordered the lower and upper limits on sides of the parameter, the middle index should give us the expected global value. 
3098          dx_param_indexes = dx_inc + 1 
3099          dx_point_index = dx_inc_sides + 1 
3100   
3101          # Find the line number. 
3102          line = 1 
3103          for i in range(1, dx_param_indexes + 1): 
3104              for j in range(1, dx_param_indexes + 1): 
3105                  for k in range(1, dx_param_indexes + 1): 
3106                      if i == dx_point_index and j == dx_point_index and k == dx_point_index: 
3107                          line_chi2 = line 
3108                      # Add to line counter. 
3109                      line += 1 
3110   
3111          # Define temporary folder. 
3112          result_dir = self.tmpdir 
3113   
3114          # For testing. 
3115          #result_dir = None 
3116          #lower = None 
3117          #upper = None 
3118          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3119   
3120   
3121          # Then do the map. 
3122          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point) 
3123   
3124          # Print where to locate values. 
3125          nr_chi2_val = dx_param_indexes**3 
3126          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3127          print("Global chi2=%3.3f, Calc_chi=%3.3f, map_line_chi2=%i" % (pre_chi2, calc_chi2, line_chi2) ) 
3128   
3129          ## Check for file creation 
3130          # Set filepaths. 
3131          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3132          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3133          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3134          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3135   
3136          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3137          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3138   
3139          # Test the files exists. 
3140          self.assert_(access(map_cfg, F_OK)) 
3141          self.assert_(access(map_net, F_OK)) 
3142          self.assert_(access(map_general, F_OK)) 
3143          self.assert_(access(point_general, F_OK)) 
3144          self.assert_(access(point_point, F_OK)) 
3145   
3146          # Open the file, and assert the chi2 value is as expected. 
3147          get_data = extract_data(file=map_name) 
3148   
3149          # Extract line 0, column 0. 
3150          test = float(get_data[line_chi2-1][0]) 
3151   
3152          # Assert. 
3153          self.assertAlmostEqual(test, pre_chi2,  6) 
3154   
3155   
3156 -    def test_dx_map_clustered_create_par_file(self): 
3157          """Test making dx_map for residues under clustered calculation, and the creation of the parameter file. 
3158   
3159          U{Task #7860<https://gna.org/task/index.php?7860>} : When dx_map is issued, create a parameter file which maps parameters to chi2 value. 
3160   
3161          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
3162          """ 
3163   
3164          # Define path to data  
3165          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'surface_chi2_clustered_fitting' 
3166   
3167          # Read data. 
3168          self.interpreter.results.read(prev_data_path + sep + 'coMDD_-_TSMFK01_-_min_-_32_-_free_spins.bz2') 
3169   
3170          # Get residue of interest. 
3171          cur_spin_id = ":%i@%s"%(65, 'N') 
3172          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3173   
3174          # Get the spin container. 
3175          cur_spin = return_spin(cur_spin_id) 
3176   
3177          # Get the chi2 value 
3178          pre_chi2 = cur_spin.chi2 
3179   
3180          # Then do a local minimisation. 
3181          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3182          self.interpreter.minimise.calculate() 
3183   
3184          # Get the chi2 value after calculation. 
3185          calc_chi2 = cur_spin.chi2 
3186   
3187          # Assert calculation is equal. 
3188          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3189   
3190          # Define dx.map settings. 
3191          dx_inc = 2 
3192          dx_params = ['dw', 'k_AB', 'r2a'] 
3193          dx_point_clustered_min = [cur_spin.dw, cur_spin.k_AB, cur_spin.r2a['SQ CPMG - 499.86214000 MHz']] 
3194   
3195          print("Params for dx map is") 
3196          print(dx_params) 
3197          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3198          print(dx_point_clustered_min) 
3199   
3200          # Define file_names. 
3201          cur_model = 'TSMFK01' 
3202          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3203          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3204   
3205          # Determine bounds for lower and upper 
3206          lower = [dx_point_clustered_min[0], dx_point_clustered_min[1], dx_point_clustered_min[2]] 
3207          upper = [19.0, 2.4, 9.5] 
3208   
3209          # Define temporary folder. 
3210          result_dir = self.tmpdir 
3211   
3212          # For testing. 
3213          #result_dir = None 
3214          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3215   
3216          # Then do the map. 
3217          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point, create_par_file=True) 
3218   
3219          # Print where to locate values. 
3220          nr_chi2_val = (dx_inc + 1)**3 
3221          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3222          print("Global chi2=%3.3f, Calc_chi=%3.3f" % (pre_chi2, calc_chi2) ) 
3223   
3224          ## Check for file creation 
3225          # Set filepaths. 
3226          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3227          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3228          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3229          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3230          map_par = get_file_path(file_name=file_name_map+".par", dir=result_dir) 
3231   
3232          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3233          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3234   
3235          # Test the files exists. 
3236          self.assert_(access(map_cfg, F_OK)) 
3237          self.assert_(access(map_net, F_OK)) 
3238          self.assert_(access(map_general, F_OK)) 
3239          self.assert_(access(map_par, F_OK)) 
3240          self.assert_(access(point_general, F_OK)) 
3241          self.assert_(access(point_point, F_OK)) 
3242   
3243          print("\nParams for dx map is") 
3244          print(dx_params) 
3245          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3246          print(dx_point_clustered_min, "\n") 
3247   
3248          # Open the parameter chi2 file, and assert the chi2 value in the sorted parameter file is not lower that than the global minimisation. 
3249          get_data = extract_data(file=map_par) 
3250   
3251          # Extract line 1, column 9. 
3252          test = float(get_data[1][9]) 
3253   
3254          # Print data if map contain a lower value than the global minimised value. 
3255          if test < pre_chi2: 
3256              print("\nInitial clustered minimised chi2 value is=%3.3f, whereby the minimum map value is=%3.3f\n" % (pre_chi2, test)) 
3257              for line in get_data: 
3258                  print(line) 
3259   
3260          # Assert that the initial global chi2 is lower than the map value. 
3261   
3262          # The following test was taken out, since this a particular interesting case. 
3263          # There exist a double minimum, where relax has not found the global minimum. 
3264          # This is due to not grid searching for R2A, but using the minimum  
3265          #self.assert_(pre_chi2 < test) 
3266   
3267   
3268 -    def test_estimate_r2eff_err(self): 
3269          """Test the user function for estimating R2eff errors from exponential curve fitting. 
3270   
3271          This follows Task 7822. 
3272          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3273   
3274          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3275          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3276          """ 
3277   
3278          # Cluster residues 
3279          cluster_ids = [ 
3280          ":13@N", 
3281          ":15@N", 
3282          ":16@N", 
3283          ":25@N", 
3284          ":26@N", 
3285          ":28@N", 
3286          ":39@N", 
3287          ":40@N", 
3288          ":41@N", 
3289          ":43@N", 
3290          ":44@N", 
3291          ":45@N", 
3292          ":49@N", 
3293          ":52@N", 
3294          ":53@N"] 
3295   
3296          # Load the data. 
3297          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3298   
3299          # The dispersion models. 
3300          MODELS = [MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3301   
3302          # The grid search size (the number of increments per dimension). 
3303          GRID_INC = None 
3304   
3305          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3306          MC_NUM = 3 
3307   
3308          # Model selection technique. 
3309          MODSEL = 'AIC' 
3310   
3311          # Execute the auto-analysis (fast). 
3312          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3313          OPT_FUNC_TOL = 1e-25 
3314          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3315          OPT_MAX_ITERATIONS = 10000000 
3316          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3317   
3318          result_dir_name = ds.tmpdir 
3319   
3320          # Make all spins free 
3321          for curspin in cluster_ids: 
3322              self.interpreter.relax_disp.cluster('free spins', curspin) 
3323              # Shut them down 
3324              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
3325   
3326          # Select only a subset of spins for global fitting 
3327          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3328          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3329   
3330          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3331          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3332   
3333          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3334          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3335   
3336          # Set the model. 
3337          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3338   
3339          # Check if intensity errors have already been calculated. 
3340          check_intensity_errors() 
3341   
3342          # Do a grid search. 
3343          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
3344   
3345          # Minimise. 
3346          self.interpreter.minimise.execute(min_algor='Newton', constraints=False, verbosity=1) 
3347   
3348          # Estimate R2eff errors. 
3349          self.interpreter.relax_disp.r2eff_err_estimate() 
3350   
3351          r1_fit = True 
3352   
3353          # Run the analysis. 
3354          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3355   
3356          # Verify the data. 
3357          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3358   
3359   
3360 -    def test_estimate_r2eff_err_auto(self): 
3361          """Test the user function for estimating R2eff errors from exponential curve fitting, via the auto_analyses menu. 
3362   
3363          This follows Task 7822. 
3364          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3365   
3366          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3367          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3368          """ 
3369   
3370          # Cluster residues 
3371          cluster_ids = [ 
3372          ":13@N", 
3373          ":15@N", 
3374          ":16@N", 
3375          ":25@N", 
3376          ":26@N", 
3377          ":28@N", 
3378          ":39@N", 
3379          ":40@N", 
3380          ":41@N", 
3381          ":43@N", 
3382          ":44@N", 
3383          ":45@N", 
3384          ":49@N", 
3385          ":52@N", 
3386          ":53@N"] 
3387   
3388          # Load the data. 
3389          #self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3390          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
3391   
3392          # Set pipe name, bundle and type. 
3393          pipe_name = 'base pipe' 
3394          pipe_bundle = 'relax_disp' 
3395          pipe_type = 'relax_disp' 
3396   
3397          # Create the data pipe. 
3398          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
3399   
3400          file = data_path + '1_setup_r1rho_GUI.py' 
3401          self.interpreter.script(file=file, dir=None) 
3402   
3403          # The dispersion models. 
3404          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3405   
3406          # The grid search size (the number of increments per dimension). 
3407          GRID_INC = None 
3408   
3409          # The number of Monte Carlo simulations to be used for error analysis for exponential curve fitting of R2eff. 
3410          # When set to minus 1, estimation of the errors will be extracted from the covariance matrix. 
3411          # This is HIGHLY likely to be wrong, but can be used in an initial test fase. 
3412          EXP_MC_NUM = -1 
3413   
3414          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3415          MC_NUM = 3 
3416   
3417          # Model selection technique. 
3418          MODSEL = 'AIC' 
3419   
3420          # Execute the auto-analysis (fast). 
3421          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3422          OPT_FUNC_TOL = 1e-25 
3423          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3424          OPT_MAX_ITERATIONS = 10000000 
3425          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3426   
3427          # Make all spins free 
3428          #for curspin in cluster_ids: 
3429          #    self.interpreter.relax_disp.cluster('free spins', curspin) 
3430          #    # Shut them down 
3431          #    self.interpreter.deselect.spin(spin_id=curspin, boolean='OR', change_all=False) 
3432   
3433          # Make all spins free 
3434          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
3435   
3436          # Select only a subset of spins for global fitting 
3437          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3438          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3439   
3440          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3441          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3442   
3443          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3444          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3445   
3446          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3447              print(spin_id) 
3448   
3449          result_dir_name = self.tmpdir 
3450          r1_fit = True 
3451   
3452          # Run the analysis. 
3453          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=EXP_MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3454   
3455          # Verify the data. 
3456          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3457   
3458   
3459 -    def test_estimate_r2eff_err_methods(self): 
3460          """Test the user function for estimating R2eff and associated errors for exponential curve fitting with different methods. 
3461          This is compared with a run where erros are estimated by 2000 Monte Carlo simulations. 
3462   
3463          This follows Task 7822. 
3464          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3465   
3466          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3467          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3468   
3469          NOTE: The difference in the methods was due to a bug in relax! 
3470          U{bug #22554<https://gna.org/bugs/index.php?22554>}. The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected. 
3471   
3472          This dataset is old, and includes 2000 Monte-Carlo simulations, which is performed wrong. 
3473          """ 
3474   
3475          # Define data path. 
3476          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
3477   
3478          # Create pipe. 
3479          self.interpreter.pipe.create('MC_2000', 'relax_disp') 
3480   
3481          # Read results for 2000 MC simulations. 
3482          self.interpreter.results.read(prev_data_path + sep + 'results') 
3483   
3484          # Start dic. 
3485          my_dic = {} 
3486          param_key_list = [] 
3487   
3488          # Do boot strapping ? 
3489          do_boot = True 
3490          if do_boot: 
3491              min_algor = 'Newton' 
3492              min_options = () 
3493              sim_boot = 200 
3494              scaling_list = [1.0, 1.0] 
3495   
3496          # First check sim values. 
3497          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3498              # Add key to dic. 
3499              my_dic[spin_id] = {} 
3500   
3501              # Loop over sim. 
3502              for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3503                  # Loop over all exp type. 
3504                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3505                      # Generate the param_key. 
3506                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3507                      r2eff_sim_point = r2eff_sim[param_key] 
3508                      i0_sim_point = cur_spin.r2eff_sim[i][param_key] 
3509   
3510                      # Assert point are higher than 0.0. 
3511                      #point_info = "r2eff=%3.2f i0=%3.2f, at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f, at sim index %i." % (r2eff_sim_point, i0_sim_point, frq/1E6, offset, point, i) 
3512                      #print(point_info) 
3513                      self.assert_(r2eff_sim_point > 0.0) 
3514                      self.assert_(i0_sim_point > 0.0) 
3515   
3516          # Get the data. 
3517          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3518              # Generate spin string. 
3519              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3520   
3521              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3522                  # Generate the param_key. 
3523                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3524   
3525                  # Loop over all sim, and collect data. 
3526                  r2eff_sim_l = [] 
3527                  i0_sim_l = [] 
3528                  for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3529                      i0_sim = cur_spin.i0_sim[i] 
3530   
3531                      r2eff_sim_i = r2eff_sim[param_key] 
3532                      r2eff_sim_l.append(r2eff_sim_i) 
3533                      i0_sim_i = i0_sim[param_key] 
3534                      i0_sim_l.append(i0_sim_i) 
3535   
3536                  # Take the standard deviation of all values. 
3537                  r2eff_sim_err = std(asarray(r2eff_sim_l), ddof=1) 
3538                  i0_sim_err = std(asarray(i0_sim_l), ddof=1) 
3539   
3540                  # Append key. 
3541                  param_key_list.append(param_key) 
3542   
3543                  # Add key to dic. 
3544                  my_dic[spin_id][param_key] = {} 
3545   
3546                  # Get the value. 
3547                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
3548                  r2eff_err = getattr(cur_spin, 'r2eff_err')[param_key] 
3549                  i0 = getattr(cur_spin, 'i0')[param_key] 
3550                  i0_err = getattr(cur_spin, 'i0_err')[param_key] 
3551   
3552                  # Save to dic. 
3553                  my_dic[spin_id][param_key]['r2eff'] = r2eff 
3554                  my_dic[spin_id][param_key]['r2eff_err'] = r2eff_err 
3555                  my_dic[spin_id][param_key]['i0'] = i0 
3556                  my_dic[spin_id][param_key]['i0_err'] = i0_err 
3557                  my_dic[spin_id][param_key]['r2eff_err_sim'] = r2eff_sim_err 
3558                  my_dic[spin_id][param_key]['i0_err_sim'] = i0_sim_err 
3559   
3560                  # Assert values are equal 
3561                  self.assertAlmostEqual(r2eff_sim_err, r2eff_err) 
3562                  self.assertAlmostEqual(i0_sim_err, i0_err) 
3563   
3564                  if do_boot: 
3565                      values = [] 
3566                      errors = [] 
3567                      times = [] 
3568                      for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
3569                          values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
3570                          errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
3571                          times.append(time) 
3572   
3573                      # Convert to numpy array. 
3574                      values = asarray(values) 
3575                      errors = asarray(errors) 
3576                      times = asarray(times) 
3577   
3578                      R_m_sim_l = [] 
3579                      I0_m_sim_l = [] 
3580                      for j in range(sim_boot): 
3581                          if j in range(0, 100000, 100): 
3582                              print("Simulation %i"%j) 
3583                          # Start minimisation. 
3584   
3585                          # Produce errors 
3586                          I_err = [] 
3587                          for j, error in enumerate(errors): 
3588                              I_error = gauss(values[j], error) 
3589                              I_err.append(I_error) 
3590                          # Convert to numpy array. 
3591                          I_err = asarray(I_err) 
3592   
3593                          x0 = [r2eff, i0] 
3594                          model = Relax_fit_opt(model='exp', num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3595   
3596                          params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, full_output=True, print_flag=0) 
3597                          R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
3598                          R_m_sim_l.append(R_m_sim_j) 
3599                          I0_m_sim_l.append(I0_m_sim_j) 
3600   
3601                      # Get stats on distribution. 
3602                      sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
3603                      sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
3604                      my_dic[spin_id][param_key]['r2eff_err_boot'] = sigma_R_sim 
3605                      my_dic[spin_id][param_key]['i0_err_boot'] = sigma_I0_sim 
3606   
3607   
3608          # A new data pipe. 
3609          self.interpreter.pipe.copy(pipe_from='MC_2000', pipe_to='r2eff_est') 
3610          self.interpreter.pipe.switch(pipe_name='r2eff_est') 
3611   
3612          # Delete old errors. 
3613          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3614              delattr(cur_spin, 'r2eff_err') 
3615              delattr(cur_spin, 'i0_err') 
3616   
3617          # Set the model. 
3618          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3619   
3620          # Estimate R2eff and errors. 
3621          self.interpreter.relax_disp.r2eff_err_estimate(verbosity=0) 
3622   
3623          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3624              # Generate spin string. 
3625              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3626   
3627              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3628                  # Generate the param_key. 
3629                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3630   
3631                  # Get the value. 
3632                  r2eff_est = getattr(cur_spin, 'r2eff')[param_key] 
3633                  r2eff_err_est = getattr(cur_spin, 'r2eff_err')[param_key] 
3634                  i0_est = getattr(cur_spin, 'i0')[param_key] 
3635                  i0_err_est = getattr(cur_spin, 'i0_err')[param_key] 
3636   
3637                  # Get from dic. 
3638                  r2eff = my_dic[spin_id][param_key]['r2eff'] 
3639                  r2eff_err = my_dic[spin_id][param_key]['r2eff_err'] 
3640                  i0 = my_dic[spin_id][param_key]['i0'] 
3641                  i0_err = my_dic[spin_id][param_key]['i0_err'] 
3642                  r2eff_sim_err = my_dic[spin_id][param_key]['r2eff_err_sim'] 
3643                  i0_sim_err = my_dic[spin_id][param_key]['i0_err_sim'] 
3644   
3645                  if do_boot: 
3646                      r2eff_boot_err = my_dic[spin_id][param_key]['r2eff_err_boot'] 
3647                      i0_boot_err = my_dic[spin_id][param_key]['i0_err_boot'] 
3648                  else: 
3649                      r2eff_boot_err = 0.0 
3650                      i0_boot_err = 0.0 
3651   
3652                  print("%s at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f." % (exp_type, frq/1E6, offset, point) ) 
3653                  print("r2eff=%3.3f/%3.3f r2eff_err=%3.4f/%3.4f/%3.4f/%3.4f" % (r2eff, r2eff_est, r2eff_err, r2eff_err_est, r2eff_sim_err, r2eff_boot_err) ), 
3654                  print("i0=%3.3f/%3.3f i0_err=%3.4f/%3.4f/%3.4f/%3.4f\n" % (i0, i0_est, i0_err, i0_err_est, i0_sim_err, i0_boot_err) ) 
3655   
3656   
3657          # Now do it manually. 
3658          estimate_r2eff(method='scipy.optimize.leastsq') 
3659   
3660          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=False) 
3661          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=True) 
3662   
3663          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=False) 
3664          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=True) 
3665   
3666          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=False) 
3667          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=True) 
3668   
3669          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=False) 
3670          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=True) 
3671   
3672          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=False) 
3673          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=True) 
3674   
3675   
3676   
3677 -    def test_exp_fit(self): 
3678          """Test the relaxation dispersion 'exp_fit' model curve fitting.""" 
3679   
3680          # Execute the script. 
3681          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'exp_fit.py') 
3682   
3683          # The original exponential curve parameters. 
3684          res_data = [ 
3685              [15., 10., 20000., 25000.], 
3686              [12., 11., 50000., 51000.], 
3687              [17., 9., 100000., 96000.] 
3688          ] 
3689   
3690          # List of parameters which do not belong to the model. 
3691          blacklist = ['cpmg_frqs', 'r2', 'rex', 'kex', 'r2a', 'k_AB', 'dw'] 
3692   
3693          # Checks for each residue. 
3694          for i in range(len(res_data)): 
3695              # Printout. 
3696              print("\nResidue number %s." % (i+1)) 
3697   
3698              # Check the fitted parameters. 
3699              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_1000.000'], res_data[i][0], places=2) 
3700              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_2000.000'], res_data[i][1], places=2) 
3701              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_1000.000']/10000, res_data[i][2]/10000, places=3) 
3702              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_2000.000']/10000, res_data[i][3]/10000, places=3) 
3703   
3704              # Check the simulation errors. 
3705              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_1000.000'] < 5.0) 
3706              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_2000.000'] < 5.0) 
3707              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_1000.000']/10000 < 5.0) 
3708              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_2000.000']/10000 < 5.0) 
3709   
3710              # Check that certain parameters are not present. 
3711              for param in blacklist: 
3712                  print("\tChecking for the absence of the '%s' parameter." % param) 
3713                  self.assert_(not hasattr(cdp.mol[0].res[i].spin[0], param)) 
3714   
3715          # Check the clustering information. 
3716          self.assert_(hasattr(cdp, 'clustering')) 
3717          keys = ['free spins', 'cluster'] 
3718          for key in keys: 
3719              self.assert_(key in cdp.clustering) 
3720          self.assert_('test' not in cdp.clustering) 
3721          self.assertEqual(cdp.clustering['free spins'], [':2@N']) 
3722          self.assertEqual(cdp.clustering['cluster'], [':1@N', ':3@N']) 
3723   
3724   
3725 -    def test_finite_value(self): 
3726          """Test return from C code, when parameters are wrong.  This can happen, if minfx takes a wrong step.""" 
3727   
3728          times = array([ 0.7,  1.,  0.8,  0.4,  0.9]) 
3729          I = array([ 476.76174875,  372.43328777,  454.20339981,  656.87936253,  419.16726341]) 
3730          errors = array([  9.48032653,  11.34093541,   9.35149017,  10.84867928,  12.17590736]) 
3731   
3732          scaling_list = [1.0, 1.0] 
3733          model = Relax_fit_opt(model='exp', num_params=2, values=I, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3734   
3735          R = - 500. 
3736          I0 = 1000. 
3737          params = [R, I0] 
3738   
3739          chi2 = model.func(params) 
3740   
3741          print("The chi2 value returned from C-code for R=%3.2f and I0=%3.2f, then chi2=%3.2f"%(R, I0, chi2)) 
3742          self.assertNotEqual(chi2, inf) 
3743   
3744   
3745 -    def test_hansen_catia_input(self): 
3746          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CATIA. 
3747   
3748          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3749          """ 
3750   
3751          # Load the R2eff results file. 
3752          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
3753          self.interpreter.results.read(file_name) 
3754          self.interpreter.deselect.spin(':4') 
3755   
3756          # The spin isotopes. 
3757          self.interpreter.spin.isotope("15N") 
3758   
3759          # Generate the input files. 
3760          self.interpreter.relax_disp.catia_input(dir=ds.tmpdir, force=True) 
3761   
3762          # Check the r2eff set files. 
3763          print("\nChecking the R2eff input set files.") 
3764          files = ['data_set_500.inp', 'data_set_500.inp'] 
3765          for file in files: 
3766              self.assert_(access(ds.tmpdir+sep+file, F_OK)) 
3767          data_set_500 = [ 
3768              "ID=500\n", 
3769              "Sfrq = 500\n", 
3770              "Temperature = 0.0\n", 
3771              "Nucleus = N15\n", 
3772              "Couplednucleus = H1\n", 
3773              "Time_equil = 0.0\n", 
3774              "Pwx_cp = 0.0\n", 
3775              "Taub = 0.0\n", 
3776              "Time_T2 = 0.03\n", 
3777              "Xcar = 0.0\n", 
3778              "Seqfil = CW_CPMG\n", 
3779              "Minerror = (2.%;0.5/s)\n", 
3780              "Basis = (Iph_7)\n", 
3781              "Format = (0;1;2)\n", 
3782              "DataDirectory = /tmp/tmpNjOGNG/input_r2eff\n", 
3783              "Data = (\n", 
3784              " [70N;spin_70_N_500.cpmg];\n", 
3785              " [71N;spin_71_N_500.cpmg];\n", 
3786              ")\n", 
3787          ] 
3788          file = open(ds.tmpdir+sep+files[0]) 
3789          lines = file.readlines() 
3790          file.close() 
3791          for i in range(len(data_set_500)): 
3792              # Skip the data directory, as this is a random file name. 
3793              if i == 14: 
3794                  continue 
3795   
3796              self.assertEqual(data_set_500[i], lines[i]) 
3797   
3798          # Check the r2eff files. 
3799          print("\nChecking the R2eff input files.") 
3800          files = ['spin_70_N_500.cpmg', 'spin_70_N_800.cpmg', 'spin_71_N_500.cpmg', 'spin_71_N_800.cpmg'] 
3801          for file in files: 
3802              self.assert_(access(ds.tmpdir+sep+'input_r2eff'+sep+file, F_OK)) 
3803          spin_70_N_500 = [ 
3804              "#        nu_cpmg(Hz)              R2(1/s)              Esd(R2)\n", 
3805              "  66.666600000000003   16.045540885533605    0.310924686180635\n", 
3806              " 133.333300000000008   14.877924861181727    0.303217270671013\n", 
3807              " 200.000000000000000   14.357820247260586    0.299894424543361\n", 
3808              " 266.666600000000017   12.664494620416516    0.289532060485796\n", 
3809              " 333.333300000000008   12.363204802467891    0.287759631749322\n", 
3810              " 400.000000000000000   11.092532381134513    0.280514035409862\n", 
3811              " 466.666600000000017   10.566090057649893    0.277618625949722\n", 
3812              " 533.333300000000008    9.805806894657803    0.273544382200754\n", 
3813              " 600.000000000000000    9.564300692201730    0.272276309984954\n", 
3814              " 666.666600000000017    9.015633750407980    0.269441511838159\n", 
3815              " 733.333300000000008    8.607764958055581    0.267375134391053\n", 
3816              " 800.000000000000000    8.279997179221338    0.265739551961997\n", 
3817              " 866.666600000000017    8.474535940963516    0.266707642726566\n", 
3818              " 933.333300000000008    8.158972897365194    0.265141210539941\n", 
3819              "1000.000000000000000    7.988630509501972    0.264304105548559\n", 
3820          ] 
3821          file = open(ds.tmpdir+sep+'input_r2eff'+sep+files[0]) 
3822          lines = file.readlines() 
3823          file.close() 
3824          for i in range(len(lines)): 
3825              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
3826          for i in range(len(spin_70_N_500)): 
3827              self.assertEqual(spin_70_N_500[i], lines[i]) 
3828   
3829          # Check the main file. 
3830          print("\nChecking the main CATIA execution file.") 
3831          main_file = [ 
3832              "ReadDataset(data_set_500.inp)\n", 
3833              "ReadDataset(data_set_800.inp)\n", 
3834              "ReadParam_Global(ParamGlobal.inp)\n", 
3835              "ReadParam_Local(ParamSet1.inp)\n", 
3836              "\n", 
3837              "FreeLocalParam(all;Omega;false)\n", 
3838              "FreeLocalParam(all;R1iph_500;false)\n", 
3839              "FreeLocalParam(all;R1iph_800;false)\n", 
3840              "\n", 
3841              "Minimize(print=y;tol=1e-25;maxiter=10000000)\n", 
3842              "\n", 
3843              "PrintParam(output/GlobalParam.fit;global)\n", 
3844              "PrintParam(output/DeltaOmega.fit;DeltaO)\n", 
3845              "PrintData(output/)\n", 
3846              "\n", 
3847              "ChiSq(all;all)\n", 
3848              "exit(0)\n" 
3849          ] 
3850          file = open("%s%sFit.catia" % (ds.tmpdir, sep)) 
3851          lines = file.readlines() 
3852          file.close() 
3853          for i in range(len(main_file)): 
3854              self.assertEqual(main_file[i], lines[i]) 
3855   
3856   
3857 -    def test_hansen_cpmg_data_auto_analysis(self): 
3858          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3859   
3860          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3861          """ 
3862   
3863          # Set the model. 
3864          ds.models = [ 
3865              MODEL_NOREX, 
3866              MODEL_LM63, 
3867              MODEL_CR72, 
3868              MODEL_IT99 
3869          ] 
3870   
3871          # Execute the script. 
3872          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
3873          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
3874   
3875          # The R20 keys. 
3876          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3877          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3878   
3879          # The 'No Rex' model checks. 
3880          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
3881          spin70 = return_spin(":70") 
3882          spin71 = return_spin(":71") 
3883          print("\n\nOptimised parameters:\n") 
3884          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3885          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3886          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3887          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3888          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
3889          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
3890          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
3891          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
3892          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
3893          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
3894   
3895          # The 'LM63' model checks. 
3896          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
3897          spin70 = return_spin(":70") 
3898          spin71 = return_spin(":71") 
3899          print("\n\nOptimised parameters:\n") 
3900          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3901          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3902          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3903          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
3904          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3905          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3906          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
3907          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
3908          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
3909          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
3910          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
3911          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
3912          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
3913          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
3914          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
3915          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
3916   
3917          # The 'CR72' model checks. 
3918          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
3919          spin70 = return_spin(":70") 
3920          spin71 = return_spin(":71") 
3921          print("\n\nOptimised parameters:\n") 
3922          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3923          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3924          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3925          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
3926          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
3927          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3928          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3929          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
3930          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
3931          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
3932          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
3933          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
3934          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
3935          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
3936          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
3937          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
3938          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
3939          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
3940          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
3941   
3942   
3943 -    def test_hansen_cpmg_data_auto_analysis_numeric(self): 
3944          """Test of the numeric model only dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3945   
3946          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3947          """ 
3948   
3949          # Set the model and numeric flag. 
3950          ds.models = [ 
3951              MODEL_NOREX, 
3952              MODEL_CR72, 
3953              MODEL_NS_CPMG_2SITE_EXPANDED 
3954          ] 
3955          ds.numeric_only = True 
3956   
3957          # Execute the script. 
3958          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
3959   
3960          # The R20 keys. 
3961          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3962          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3963   
3964          # The 'No Rex' model checks. 
3965          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
3966          spin70 = return_spin(":70") 
3967          spin71 = return_spin(":71") 
3968          print("\n\nOptimised parameters:\n") 
3969          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3970          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3971          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3972          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3973          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
3974          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
3975          self.assertAlmostEqual(spin70.chi2/10000, 8973.84810025761/10000, 3) 
3976          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
3977          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
3978          self.assertAlmostEqual(spin71.chi2/10000, 3908.00127830003/10000, 3) 
3979   
3980          # The 'CR72' model checks. 
3981          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
3982          spin70 = return_spin(":70") 
3983          spin71 = return_spin(":71") 
3984          print("\n\nOptimised parameters:\n") 
3985          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3986          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3987          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3988          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
3989          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
3990          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3991          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3992          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
3993          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
3994          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
3995          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
3996          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
3997          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
3998          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
3999          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4000          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4001          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4002          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4003          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4004   
4005          # The 'NS CPMG 2-site expanded' model checks. 
4006          self.interpreter.pipe.switch(pipe_name='NS CPMG 2-site expanded - relax_disp') 
4007          spin70 = return_spin(":70") 
4008          spin71 = return_spin(":71") 
4009          print("\n\nOptimised parameters:\n") 
4010          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4011          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4012          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4013          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4014          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4015          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4016          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4017          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95815351460902, 3) 
4018          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39649535771294, 3) 
4019          self.assertAlmostEqual(spin70.pA, 0.989701014493195, 3) 
4020          self.assertAlmostEqual(spin70.dw, 5.67314464776128, 3) 
4021          self.assertAlmostEqual(spin70.kex/10000, 1713.65380495429/10000, 3) 
4022          self.assertAlmostEqual(spin70.chi2, 52.5106880917473, 3) 
4023          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99889337382435, 3) 
4024          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89822887466673, 3) 
4025          self.assertAlmostEqual(spin71.pA, 0.986709050819695, 3) 
4026          self.assertAlmostEqual(spin71.dw, 2.09238266766502, 2) 
4027          self.assertAlmostEqual(spin71.kex/10000, 2438.27019901422/10000, 3) 
4028          self.assertAlmostEqual(spin71.chi2, 15.1644906963987, 3) 
4029   
4030          # The final data pipe checks. 
4031          self.interpreter.pipe.switch(pipe_name='final - relax_disp') 
4032          spin70 = return_spin(":70") 
4033          spin71 = return_spin(":71") 
4034          self.assertEqual(spin70.model, 'NS CPMG 2-site expanded') 
4035          self.assertEqual(spin71.model, 'NS CPMG 2-site expanded') 
4036   
4037   
4038 -    def test_hansen_cpmg_data_auto_analysis_r2eff(self): 
4039          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data (using the R2eff data directly instead of peak intensities). 
4040   
4041          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4042          """ 
4043   
4044          # Set the model. 
4045          ds.models = [ 
4046              MODEL_NOREX, 
4047              MODEL_LM63, 
4048              MODEL_CR72, 
4049              MODEL_IT99 
4050          ] 
4051   
4052          # Execute the script. 
4053          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_r2eff_data.py') 
4054          self.interpreter.state.save('analysis_r2eff', dir=ds.tmpdir, force=True) 
4055   
4056          # The R20 keys. 
4057          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4058          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4059   
4060          # The 'No Rex' model checks. 
4061          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4062          spin70 = return_spin(":70") 
4063          spin71 = return_spin(":71") 
4064          print("\n\nOptimised parameters:\n") 
4065          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4066          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4067          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4068          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4069          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4070          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4071          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
4072          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4073          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4074          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
4075   
4076          # The 'LM63' model checks. 
4077          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
4078          spin70 = return_spin(":70") 
4079          spin71 = return_spin(":71") 
4080          print("\n\nOptimised parameters:\n") 
4081          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4082          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4083          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4084          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4085          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4086          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4087          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
4088          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
4089          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
4090          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
4091          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
4092          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
4093          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
4094          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
4095          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
4096          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
4097   
4098          # The 'CR72' model checks. 
4099          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4100          spin70 = return_spin(":70") 
4101          spin71 = return_spin(":71") 
4102          print("\n\nOptimised parameters:\n") 
4103          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4104          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4105          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4106          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4107          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4108          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4109          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4110          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4111          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4112          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4113          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4114          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4115          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4116          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00317154730225, 3) 
4117          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797713541, 3) 
4118          self.assertAlmostEqual(spin71.pA, 0.985922406429147, 3) 
4119          self.assertAlmostEqual(spin71.dw, 2.00500965887772, 2) 
4120          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579804/10000, 3) 
4121          self.assertAlmostEqual(spin71.chi2, 15.6595374288635, 3) 
4122   
4123   
4124 -    def test_hansen_cpmg_data_missing_auto_analysis(self): 
4125          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data with parts missing. 
4126   
4127          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4128          """ 
4129   
4130          # Set the model. 
4131          ds.models = [ 
4132              MODEL_R2EFF, 
4133              MODEL_NOREX, 
4134              MODEL_CR72, 
4135              MODEL_NS_CPMG_2SITE_EXPANDED 
4136          ] 
4137   
4138          # Execute the script. 
4139          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data_missing.py') 
4140          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
4141   
4142          # The R20 keys. 
4143          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4144          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4145   
4146          # The 'No Rex' model checks. 
4147          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4148          spin4 = return_spin(":4") 
4149          spin70 = return_spin(":70") 
4150          spin71 = return_spin(":71") 
4151          print("\n\nOptimised parameters:\n") 
4152          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4153          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4154          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4155          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4156          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463084515171, 3) 
4157          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63220784651911, 3) 
4158          self.assertAlmostEqual(spin4.chi2, 26.7356700694891, 3) 
4159          self.assertAlmostEqual(spin70.r2[r20_key1], 10.534285641325, 3) 
4160          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112794857068, 3) 
4161          self.assertAlmostEqual(spin70.chi2, 8973.84809774722, 3) 
4162          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83136858890037, 3) 
4163          self.assertAlmostEqual(spin71.chi2, 182.60081909193, 3) 
4164   
4165          # The 'CR72' model checks. 
4166          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4167          spin4 = return_spin(":4") 
4168          spin70 = return_spin(":70") 
4169          spin71 = return_spin(":71") 
4170          print("\n\nOptimised parameters:\n") 
4171          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4172          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4173          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4174          print("%-20s %20.15g %20.15g %20.15g" % ("pA", spin4.pA, spin70.pA, spin71.pA)) 
4175          print("%-20s %20.15g %20.15g %20.15g" % ("dw", spin4.dw, spin70.dw, spin71.dw)) 
4176          print("%-20s %20.15g %20.15g %20.15g" % ("kex", spin4.kex, spin70.kex, spin71.kex)) 
4177          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4178          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463650370664, 2) 
4179          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63221675941434, 3) 
4180          #self.assertAlmostEqual(spin4.pA, 0.818979078699935, 3)    # As dw (and kex) is zero, this parameter is not stable. 
4181          self.assertAlmostEqual(spin4.dw, 0.0, 2) 
4182          self.assertAlmostEqual(spin4.kex/10000, 0.0, 3) 
4183          self.assertAlmostEqual(spin4.chi2/100, 26.7356711142038/100, 3) 
4184          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97268077496405, 3) 
4185          self.assertAlmostEqual(spin70.r2[r20_key2], 9.41028133407727, 3) 
4186          self.assertAlmostEqual(spin70.pA, 0.989856641885939, 3) 
4187          self.assertAlmostEqual(spin70.dw, 5.60889911049405, 3) 
4188          self.assertAlmostEqual(spin70.kex/10000, 1752.62025618632/10000, 3) 
4189          self.assertAlmostEqual(spin70.chi2, 53.8382196964083, 3) 
4190          self.assertAlmostEqual(spin71.r2[r20_key1], 4.98123328466942, 3) 
4191          self.assertAlmostEqual(spin71.pA, 0.996607425484157, 3) 
4192          self.assertAlmostEqual(spin71.dw, 4.34346257383825, 2) 
4193          self.assertAlmostEqual(spin71.kex/10000, 1936.73197158804/10000, 3) 
4194          self.assertAlmostEqual(spin71.chi2, 5.51703791653689, 3) 
4195   
4196   
4197 -    def test_hansen_cpmg_data_to_cr72(self): 
4198          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 dispersion model. 
4199   
4200          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4201          """ 
4202   
4203          # Base data setup. 
4204          self.setup_hansen_cpmg_data(model='CR72') 
4205   
4206          # Alias the spins. 
4207          spin70 = return_spin(":70") 
4208          spin71 = return_spin(":71") 
4209   
4210          # The R20 keys. 
4211          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4212          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4213   
4214          # Set the initial parameter values. 
4215          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4216          spin70.pA = 0.9 
4217          spin70.dw = 6.0 
4218          spin70.kex = 1500.0 
4219          spin71.r2 = {r20_key1: 5, r20_key2: 9.0} 
4220          spin71.pA = 0.9 
4221          spin71.dw = 4.0 
4222          spin71.kex = 1900.0 
4223   
4224          # Low precision optimisation. 
4225          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4226   
4227          # Printout. 
4228          print("\n\nOptimised parameters:\n") 
4229          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4230          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4231          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4232          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4233          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4234          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4235          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4236   
4237          # Checks for residue :70. 
4238          self.assertAlmostEqual(spin70.r2[r20_key1], 6.9724581325007, 4) 
4239          self.assertAlmostEqual(spin70.r2[r20_key2], 9.40968331038162, 2) 
4240          self.assertAlmostEqual(spin70.pA, 0.989856656702431, 4) 
4241          self.assertAlmostEqual(spin70.dw, 5.60885879594746, 3) 
4242          self.assertAlmostEqual(spin70.kex/1000, 1752.91052702273/1000, 3) 
4243          self.assertAlmostEqual(spin70.chi2, 53.8382133597495, 4) 
4244   
4245          # Checks for residue :71. 
4246          self.assertAlmostEqual(spin71.r2[r20_key1], 5.0030740940524, 4) 
4247          self.assertAlmostEqual(spin71.pA, 0.985941082507823, 4) 
4248          self.assertAlmostEqual(spin71.dw, 2.00640384113696, 4) 
4249          self.assertAlmostEqual(spin71.kex/1000, 2480.79614442041/1000, 4) 
4250          self.assertAlmostEqual(spin71.chi2, 15.6595388312451, 4) 
4251   
4252          # Test the conversion to k_AB from kex and pA. 
4253          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4254          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4255   
4256          # Test the conversion to k_BA from kex and pA. 
4257          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4258          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4259   
4260   
4261 -    def test_hansen_cpmg_data_to_cr72_full(self): 
4262          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 full dispersion model. 
4263   
4264          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4265          """ 
4266   
4267          # Base data setup. 
4268          self.setup_hansen_cpmg_data(model='CR72 full') 
4269   
4270          # Alias the spins. 
4271          spin70 = return_spin(":70") 
4272          spin71 = return_spin(":71") 
4273   
4274          # The R20 keys. 
4275          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4276          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4277   
4278          # Set the initial parameter values. 
4279          spin70.r2a = {r20_key1: 7.0, r20_key2: 9.0} 
4280          spin70.r2b = {r20_key1: 7.0, r20_key2: 9.0} 
4281          spin70.pA = 0.9 
4282          spin70.dw = 6.0 
4283          spin70.kex = 1500.0 
4284          spin71.r2a = {r20_key1: 5.0, r20_key2: 9.0} 
4285          spin71.r2b = {r20_key1: 5.0, r20_key2: 9.0} 
4286          spin71.pA = 0.9 
4287          spin71.dw = 4.0 
4288          spin71.kex = 1900.0 
4289   
4290          # Low precision optimisation. 
4291          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4292   
4293          # Printout. 
4294          print("\n\nOptimised parameters:\n") 
4295          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4296          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4297          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4298          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4299          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4300          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4301          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4302          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4303          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4304   
4305          # Checks for residue :70. 
4306          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.87485258365614, 4) 
4307          self.assertAlmostEqual(spin70.r2b[r20_key1], 1.26075839074614, 4) 
4308          self.assertAlmostEqual(spin70.r2a[r20_key2], 8.79580446260797, 4) 
4309          self.assertAlmostEqual(spin70.r2b[r20_key2], 51.188411562843, 4) 
4310          self.assertAlmostEqual(spin70.pA, 0.989384178573802, 4) 
4311          self.assertAlmostEqual(spin70.dw, 5.54738203723682, 4) 
4312          self.assertAlmostEqual(spin70.kex/1000, 1831.4566463179/1000, 4) 
4313          self.assertAlmostEqual(spin70.chi2, 50.450410782403, 4) 
4314   
4315          # Checks for residue :71. 
4316          self.assertAlmostEqual(spin71.r2a[r20_key1], 5.04185695754972, 4) 
4317          self.assertAlmostEqual(spin71.r2b[r20_key1], 1.62857899941921, 4) 
4318          self.assertAlmostEqual(spin71.pA, 0.988832866751676, 4) 
4319          self.assertAlmostEqual(spin71.dw, 2.24905251856265, 4) 
4320          self.assertAlmostEqual(spin71.kex/1000, 2397.64122642946/1000, 4) 
4321          self.assertAlmostEqual(spin71.chi2, 15.8586492923672, 4) 
4322   
4323          # Test the conversion to k_AB from kex and pA. 
4324          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4325          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4326   
4327          # Test the conversion to k_BA from kex and pA. 
4328          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4329          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4330   
4331   
4332 -    def test_hansen_cpmg_data_to_it99(self): 
4333          """Optimisation of Dr. Flemming Hansen's CPMG data to the IT99 dispersion model. 
4334   
4335          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4336          """ 
4337   
4338          # Base data setup. 
4339          self.setup_hansen_cpmg_data(model='IT99') 
4340   
4341          # Alias the spins. 
4342          spin70 = return_spin(":70") 
4343          spin71 = return_spin(":71") 
4344   
4345          # The R20 keys. 
4346          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4347          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4348   
4349          # Set the initial parameter values. 
4350          spin70.r2 = {r20_key1: 8.8, r20_key2: 16.6} 
4351          spin70.dw = 10.0 
4352          spin70.pA = 0.5 
4353          spin70.tex = 1000.09 
4354          spin71.r2 = {r20_key1: 1.0, r20_key2: 1.0} 
4355          spin71.dw = 10.0 
4356          spin71.pA = 0.95 
4357          spin71.tex = 0.1 
4358   
4359          # Low precision optimisation. 
4360          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-10, grad_tol=None, max_iter=10000, constraints=True, scaling=True, verbosity=1) 
4361   
4362          # Printout. 
4363          print("\n\nOptimised parameters:\n") 
4364          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4365          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4366          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4367          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4368          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4369          print("%-20s %20.15g %20.15g" % ("tex", spin70.tex, spin71.tex)) 
4370          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4371   
4372          # Checks for residue :70. 
4373          self.assertAlmostEqual(spin70.r2[r20_key1], 7.24471197811838, 4) 
4374          self.assertAlmostEqual(spin70.r2[r20_key2], 10.0571040704729, 4) 
4375          self.assertAlmostEqual(spin70.dw, 5.2116923222744, 4) 
4376          self.assertAlmostEqual(spin70.pA, 0.990253627907212, 4) 
4377          self.assertAlmostEqual(spin70.tex*1000, 0.000638394793480444*1000, 4) 
4378          self.assertAlmostEqual(spin70.chi2, 93.5135798618747, 4) 
4379   
4380          # Checks for residue :71. 
4381          self.assertAlmostEqual(spin71.r2[r20_key1], 5.05971235970214, 4) 
4382          self.assertAlmostEqual(spin71.r2[r20_key2], 6.96641194493447, 4) 
4383          self.assertAlmostEqual(spin71.dw, 0.435389946897141, 4) 
4384          self.assertAlmostEqual(spin71.pA, 0.500000000213519, 3) 
4385          self.assertAlmostEqual(spin71.tex*1000, 0.000372436400585538*1000, 4) 
4386          self.assertAlmostEqual(spin71.chi2, 23.7895798801404, 4) 
4387   
4388   
4389 -    def test_hansen_cpmg_data_to_lm63(self): 
4390          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4391   
4392          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4393          """ 
4394   
4395          # Base data setup. 
4396          self.setup_hansen_cpmg_data(model='LM63') 
4397   
4398          # Alias the spins. 
4399          spin70 = return_spin(":70") 
4400          spin71 = return_spin(":71") 
4401   
4402          # The R20 keys. 
4403          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4404          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4405   
4406          # Set the initial parameter values. 
4407          spin70.r2 = {r20_key1: 7.0, r20_key2: 7.0} 
4408          spin70.phi_ex = 0.3 
4409          spin70.kex = 5000.0 
4410          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4411          spin71.phi_ex = 0.1 
4412          spin71.kex = 2500.0 
4413   
4414          # Low precision optimisation. 
4415          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4416   
4417          # Printout. 
4418          print("\n\nOptimised parameters:\n") 
4419          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4420          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4421          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4422          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4423          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4424          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4425   
4426          # Checks for residue :70. 
4427          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74362294539099) 
4428          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406797067481, 6) 
4429          self.assertAlmostEqual(spin70.phi_ex, 0.312733013751449) 
4430          self.assertAlmostEqual(spin70.kex/1000, 4723.09897146338/1000, 6) 
4431          self.assertAlmostEqual(spin70.chi2, 363.534044873483) 
4432   
4433          # Checks for residue :71. 
4434          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00776657729728, 5) 
4435          self.assertAlmostEqual(spin71.phi_ex, 0.0553787825650613, 5) 
4436          self.assertAlmostEqual(spin71.kex/1000, 2781.72292994154/1000, 5) 
4437          self.assertAlmostEqual(spin71.chi2, 17.0776399916287, 5) 
4438   
4439   
4440 -    def test_hansen_cpmg_data_to_lm63_3site(self): 
4441          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4442   
4443          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4444          """ 
4445   
4446          # Base data setup. 
4447          self.setup_hansen_cpmg_data(model='LM63 3-site') 
4448   
4449          # Alias the spins. 
4450          spin70 = return_spin(":70") 
4451          spin71 = return_spin(":71") 
4452   
4453          # The R20 keys. 
4454          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4455          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4456   
4457          ## Set the initial parameter values. 
4458          spin70.r2 = {r20_key1: 7.570370921220954, r20_key2: 8.694446951909107} 
4459          spin70.phi_ex_B = 0.14872003058250227 
4460          spin70.phi_ex_C = 0.1319419923472704 
4461          spin70.kB = 4103.672910444741 
4462          spin70.kC = 7029.001690726248 
4463          spin71.r2 = {r20_key1: 5.1347793381636, r20_key2: 7.156573986051575} 
4464          spin71.phi_ex_B = 0.04013553485505605 
4465          spin71.phi_ex_C = 0.020050748406928887 
4466          spin71.kB = 4045.3007136121364 
4467          spin71.kC = 3586.38798270774 
4468   
4469          #self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
4470          #self.interpreter.minimise.grid_search(lower=None, upper=None, inc=41, constraints=True, verbosity=1) 
4471   
4472          # Low precision optimisation. 
4473          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4474   
4475          # Printout. 
4476          print("\n\nOptimised parameters:\n") 
4477          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4478          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4479          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4480          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin70.phi_ex_B, spin71.phi_ex_B)) 
4481          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin70.phi_ex_C, spin71.phi_ex_C)) 
4482          print("%-20s %20.15g %20.15g" % ("kB", spin70.kB, spin71.kB)) 
4483          print("%-20s %20.15g %20.15g" % ("kC", spin70.kC, spin71.kC)) 
4484          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4485   
4486          # Checks for residue :70. 
4487          self.assertAlmostEqual(spin70.r2[r20_key1], 6.7436230253685, 5) 
4488          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406813008828, 6) 
4489          self.assertAlmostEqual(spin70.phi_ex_B, 0.206304023079778, 5) 
4490          self.assertAlmostEqual(spin70.phi_ex_C, 0.106428983339627, 5) 
4491          self.assertAlmostEqual(spin70.kB/1000, 4723.09897652589/1000, 6) 
4492          self.assertAlmostEqual(spin70.kC/1000, 4723.09876196409/1000, 6) 
4493          self.assertAlmostEqual(spin70.chi2, 363.534044873483, 5) 
4494   
4495          # Checks for residue :71. 
4496          self.assertAlmostEqual(spin71.r2[r20_key1], 4.96612095596752, 5) 
4497          self.assertAlmostEqual(spin71.phi_ex_B, 0.00398262266512895, 5) 
4498          self.assertAlmostEqual(spin71.phi_ex_C, 0.0555791581291262, 5) 
4499          self.assertAlmostEqual(spin71.kB/1000, 1323.33195689832/1000, 5) 
4500          self.assertAlmostEqual(spin71.kC/1000, 3149.58971568059/1000, 5) 
4501          self.assertAlmostEqual(spin71.chi2, 16.2620934464368) 
4502   
4503   
4504 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D(self): 
4505          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D' dispersion model. 
4506   
4507          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4508          """ 
4509   
4510          # Base data setup. 
4511          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D') 
4512   
4513          # Alias the spins. 
4514          spin70 = return_spin(":70") 
4515          spin71 = return_spin(":71") 
4516   
4517          # The R20 keys. 
4518          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4519          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4520   
4521          # Set the initial parameter values. 
4522          spin70.r2 = {r20_key1: 6.994165925, r20_key2: 9.428129427} 
4523          spin70.pA = 0.9897754407 
4524          spin70.dw = 5.642418428 
4525          spin70.kex = 1743.666375 
4526          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4527          spin71.pA = 0.9968032899 
4528          spin71.dw = 4.577891393 
4529          spin71.kex = 1830.044597 
4530   
4531          # Low precision optimisation. 
4532          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4533   
4534          # Printout. 
4535          print("\n\nOptimised parameters:\n") 
4536          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4537          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4538          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4539          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4540          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4541          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4542          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4543   
4544          # Checks for residue :70. 
4545          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95797760459016, 4) 
4546          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39628959312699, 4) 
4547          self.assertAlmostEqual(spin70.pA, 0.989700985380975, 4) 
4548          self.assertAlmostEqual(spin70.dw, 5.6733714171086, 4) 
4549          self.assertAlmostEqual(spin70.kex/1000, 1713.63101361545/1000, 4) 
4550          self.assertAlmostEqual(spin70.chi2, 52.5106928523775, 4) 
4551   
4552          # Checks for residue :71. 
4553          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99893565849977, 4) 
4554          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89825625944034, 4) 
4555          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 4) 
4556          self.assertAlmostEqual(spin71.dw, 2.09292495350993, 4) 
4557          self.assertAlmostEqual(spin71.kex/1000, 2438.04423541463/1000, 4) 
4558          self.assertAlmostEqual(spin71.chi2, 15.164490242352, 4) 
4559   
4560          # Test the conversion to k_AB from kex and pA. 
4561          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4562          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4563   
4564          # Test the conversion to k_BA from kex and pA. 
4565          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4566          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4567   
4568   
4569 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D_full(self): 
4570          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D full' dispersion model. 
4571   
4572          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4573          """ 
4574   
4575          # Base data setup. 
4576          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D full') 
4577   
4578          # Alias the spins. 
4579          spin70 = return_spin(":70") 
4580          spin71 = return_spin(":71") 
4581   
4582          # The R20 keys. 
4583          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4584          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4585   
4586          # Set the initial parameter values. 
4587          spin70.r2a = {r20_key1: 6.644753428, r20_key2: 7.891776687} 
4588          spin70.r2b = {r20_key1: 7.163478485, r20_key2: 138.5170395} 
4589          spin70.pA = 0.9884781357 
4590          spin70.dw = 5.456507396 
4591          spin70.kex = 1906.521189 
4592          spin71.r2a = {r20_key1: 4.99893524108981, r20_key2: 100.0} 
4593          spin71.r2b = {r20_key1: 8.27456243639973, r20_key2: 100.0} 
4594          spin71.pA = 0.986709616684097 
4595          spin71.dw = 2.09245158280905 
4596          spin71.kex = 2438.2766211401 
4597   
4598          # Low precision optimisation. 
4599          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4600   
4601          # Printout. 
4602          print("\n\nOptimised parameters:\n") 
4603          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4604          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4605          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4606          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4607          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4608          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4609          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4610          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4611          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4612   
4613          # Checks for residue :70. 
4614          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.61176004043484, 4) 
4615          self.assertAlmostEqual(spin70.r2b[r20_key1], 7.4869316381241, 4) 
4616          self.assertAlmostEqual(spin70.r2a[r20_key2], 7.78200386067591, 4) 
4617          self.assertAlmostEqual(spin70.r2b[r20_key2], 141.703593742468, 4) 
4618          self.assertAlmostEqual(spin70.pA, 0.988404987055969, 4) 
4619          self.assertAlmostEqual(spin70.dw, 5.4497360203213, 4) 
4620          self.assertAlmostEqual(spin70.kex/1000, 1934.09304607082/1000, 4) 
4621          self.assertAlmostEqual(spin70.chi2, 44.6793752187925, 4) 
4622   
4623          # Checks for residue :71. 
4624          self.assertAlmostEqual(spin71.r2a[r20_key1], 4.6013095731966, 4) 
4625          self.assertAlmostEqual(spin71.r2b[r20_key1], 13.3245678276332, 4) 
4626          self.assertAlmostEqual(spin71.r2a[r20_key2], 2.08243621257779, 4) 
4627          self.assertAlmostEqual(spin71.r2b[r20_key2], 153.355765094575, 4) 
4628          self.assertAlmostEqual(spin71.pA, 0.9665748685124, 4) 
4629          self.assertAlmostEqual(spin71.dw, 1.41898001408953, 4) 
4630          self.assertAlmostEqual(spin71.kex/1000, 2580.65795560688/1000, 4) 
4631          self.assertAlmostEqual(spin71.chi2, 13.4937006732165, 4) 
4632   
4633          # Test the conversion to k_AB from kex and pA. 
4634          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4635          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4636   
4637          # Test the conversion to k_BA from kex and pA. 
4638          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4639          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4640   
4641   
4642 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_expanded(self): 
4643          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site expanded' dispersion model. 
4644   
4645          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4646          """ 
4647   
4648          # Base data setup. 
4649          self.setup_hansen_cpmg_data(model='NS CPMG 2-site expanded') 
4650   
4651          # Alias the spins. 
4652          spin70 = return_spin(":70") 
4653          spin71 = return_spin(":71") 
4654   
4655          # The R20 keys. 
4656          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4657          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4658   
4659          # Set the initial parameter values. 
4660          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4661          spin70.pA = 0.9 
4662          spin70.dw = 6.0 
4663          spin70.kex = 1500.0 
4664          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4665          spin71.pA = 0.9 
4666          spin71.dw = 4.0 
4667          spin71.kex = 1900.0 
4668   
4669          # Low precision optimisation. 
4670          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4671   
4672          # Printout. 
4673          print("\n\nOptimised parameters:\n") 
4674          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4675          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4676          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4677          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4678          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4679          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4680          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4681   
4682          # Checks for residue :70. 
4683          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95813330991529, 4) 
4684          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39663480561524, 4) 
4685          self.assertAlmostEqual(spin70.pA, 0.989700843879574, 4) 
4686          self.assertAlmostEqual(spin70.dw, 5.67315878825691, 4) 
4687          self.assertAlmostEqual(spin70.kex/1000, 1713.56110716632/1000, 4) 
4688          self.assertAlmostEqual(spin70.chi2, 52.5106879242812, 4) 
4689   
4690          # Checks for residue :71. 
4691          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99881666793312, 4) 
4692          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89817482453042, 4) 
4693          self.assertAlmostEqual(spin71.pA, 0.986712911453639, 4) 
4694          self.assertAlmostEqual(spin71.dw, 2.09273069372236, 4) 
4695          self.assertAlmostEqual(spin71.kex/1000, 2438.20525930405/1000, 4) 
4696          self.assertAlmostEqual(spin71.chi2, 15.1644913030633, 4) 
4697   
4698          # Test the conversion to k_AB from kex and pA. 
4699          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4700          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4701   
4702          # Test the conversion to k_BA from kex and pA. 
4703          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4704          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4705   
4706   
4707 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star(self): 
4708          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star' dispersion model. 
4709   
4710          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4711          """ 
4712   
4713          # Base data setup. 
4714          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star') 
4715   
4716          # Alias the spins. 
4717          spin70 = return_spin(":70") 
4718          spin71 = return_spin(":71") 
4719   
4720          # The R20 keys. 
4721          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4722          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4723   
4724          # Set the initial parameter values. 
4725          spin70.r2 = {r20_key1: 6.996327746, r20_key2: 9.452051268} 
4726          spin70.pA = 0.9897519798 
4727          spin70.dw = 5.644862195 
4728          spin70.kex = 1723.820567 
4729          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4730          spin71.pA = 0.9968032899 
4731          spin71.dw = 4.577891393 
4732          spin71.kex = 1830.044597 
4733   
4734          # Low precision optimisation. 
4735          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4736   
4737          # Printout. 
4738          print("\n\nOptimised parameters:\n") 
4739          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4740          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4741          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4742          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4743          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4744          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4745          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4746   
4747          # Checks for residue :70. 
4748          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95543947938561, 1) 
4749          self.assertAlmostEqual(spin70.r2[r20_key2], 9.38991914134929, 1) 
4750          self.assertAlmostEqual(spin70.pA, 0.989702750971153, 3) 
4751          self.assertAlmostEqual(spin70.dw, 5.67527122494516, 1) 
4752          self.assertAlmostEqual(spin70.kex/1000, 1715.72032391817/1000, 1) 
4753          self.assertAlmostEqual(spin70.chi2, 52.5011991483842, 1) 
4754   
4755          # Checks for residue :71. 
4756          self.assertAlmostEqual(spin71.r2[r20_key1], 4.992594256544, 1) 
4757          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 2) 
4758          self.assertAlmostEqual(spin71.dw/100, 2.09292495350993/100, 2) 
4759          self.assertAlmostEqual(spin71.kex/100000, 2438.04423541463/100000, 2) 
4760          self.assertAlmostEqual(spin71.chi2/100, 15.1644902423334/100, 1) 
4761   
4762          # Test the conversion to k_AB from kex and pA. 
4763          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4764          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4765   
4766          # Test the conversion to k_BA from kex and pA. 
4767          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4768          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4769   
4770   
4771 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star_full(self): 
4772          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star full' dispersion model. 
4773   
4774          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4775          """ 
4776   
4777          # Base data setup. 
4778          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star full') 
4779   
4780          # Alias the spins. 
4781          spin70 = return_spin(":70") 
4782          spin71 = return_spin(":71") 
4783   
4784          # The R20 keys. 
4785          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4786          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4787   
4788          # Set the initial parameter values. 
4789          spin70.r2a = {r20_key1: 6.44836878645126, r20_key2: 7.00382877393494} 
4790          spin70.r2b = {r20_key1: 12.2083127421994, r20_key2: 199.862962628402} 
4791          spin70.pA = 0.987648082613451 
4792          spin70.dw = 5.30679853807572 
4793          spin70.kex = 2033.25380420666 
4794          spin71.r2a = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4795          spin71.r2b = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4796          spin71.pA = 0.992258541625787 
4797          spin71.dw = 2.75140650899058 
4798          spin71.kex = 2106.60885247431 
4799   
4800          # Low precision optimisation. 
4801          self.interpreter.minimise.calculate() 
4802   
4803          # Checks for residue :70. 
4804          self.assertAlmostEqual(spin70.chi2/10, 45.773987568491123/10, 2) 
4805          self.assertAlmostEqual(spin71.chi2/10, 17.329385665659192/10, 2) 
4806   
4807   
4808 -    def test_hansen_cpmgfit_input(self): 
4809          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CPMGFit. 
4810   
4811          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4812          """ 
4813   
4814          # Load the R2eff results file. 
4815          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
4816          self.interpreter.results.read(file_name) 
4817          self.interpreter.deselect.spin(':4') 
4818   
4819          # Set up the model. 
4820          self.interpreter.relax_disp.select_model('LM63') 
4821   
4822          # Generate the input files. 
4823          self.interpreter.relax_disp.cpmgfit_input(force=True, dir=ds.tmpdir) 
4824   
4825          # What the files should contain. 
4826          batch_file = ['#! /bin/sh\n', '\n', 'cpmgfit -grid -xmgr -f spin_70_N.in | tee spin_70_N.out\n', 'cpmgfit -grid -xmgr -f spin_71_N.in | tee spin_71_N.out\n'] 
4827          spin1 = [ 
4828              "title :70@N\n", 
4829              "fields 2 11.7432964915 18.7892743865\n", 
4830              "function CPMG\n", 
4831              "R2 1 10 20\n", 
4832              "Rex 0 100.0 100\n", 
4833              "Tau 0 10.0 100\n", 
4834              "xmgr\n", 
4835              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4836              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4837              "@ xaxis ticklabel format decimal\n", 
4838              "@ yaxis ticklabel format decimal\n", 
4839              "@ xaxis ticklabel char size 0.8\n", 
4840              "@ yaxis ticklabel char size 0.8\n", 
4841              "@ world xmin 0.0\n", 
4842              "data\n", 
4843              "0.133333             16.045541            0.310925             11.743296           \n", 
4844              "0.266667             14.877925            0.303217             11.743296           \n", 
4845              "0.400000             14.357820            0.299894             11.743296           \n", 
4846              "0.533333             12.664495            0.289532             11.743296           \n", 
4847              "0.666667             12.363205            0.287760             11.743296           \n", 
4848              "0.800000             11.092532            0.280514             11.743296           \n", 
4849              "0.933333             10.566090            0.277619             11.743296           \n", 
4850              "1.066667             9.805807             0.273544             11.743296           \n", 
4851              "1.200000             9.564301             0.272276             11.743296           \n", 
4852              "1.333333             9.015634             0.269442             11.743296           \n", 
4853              "1.466667             8.607765             0.267375             11.743296           \n", 
4854              "1.600000             8.279997             0.265740             11.743296           \n", 
4855              "1.733333             8.474536             0.266708             11.743296           \n", 
4856              "1.866667             8.158973             0.265141             11.743296           \n", 
4857              "2.000000             7.988631             0.264304             11.743296           \n", 
4858              "0.133333             22.224914            0.166231             18.789274           \n", 
4859              "0.266667             21.230874            0.162377             18.789274           \n", 
4860              "0.400000             20.603704            0.160017             18.789274           \n", 
4861              "0.533333             20.327797            0.158996             18.789274           \n", 
4862              "0.666667             18.855377            0.153719             18.789274           \n", 
4863              "0.800000             18.537531            0.152617             18.789274           \n", 
4864              "0.933333             17.508069            0.149138             18.789274           \n", 
4865              "1.066667             16.035604            0.144391             18.789274           \n", 
4866              "1.200000             15.168192            0.141717             18.789274           \n", 
4867              "1.333333             14.431802            0.139516             18.789274           \n", 
4868              "1.466667             14.034137            0.138354             18.789274           \n", 
4869              "1.600000             12.920148            0.135192             18.789274           \n", 
4870              "1.733333             12.653673            0.134456             18.789274           \n", 
4871              "1.866667             12.610864            0.134338             18.789274           \n", 
4872              "2.000000             11.969303            0.132601             18.789274           \n" 
4873          ] 
4874          spin2 = [ 
4875              "title :71@N\n", 
4876              "fields 2 11.7432964915 18.7892743865\n", 
4877              "function CPMG\n", 
4878              "R2 1 10 20\n", 
4879              "Rex 0 100.0 100\n", 
4880              "Tau 0 10.0 100\n", 
4881              "xmgr\n", 
4882              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4883              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4884              "@ xaxis ticklabel format decimal\n", 
4885              "@ yaxis ticklabel format decimal\n", 
4886              "@ xaxis ticklabel char size 0.8\n", 
4887              "@ yaxis ticklabel char size 0.8\n", 
4888              "@ world xmin 0.0\n", 
4889              "data\n", 
4890              "0.133333             7.044342             0.170035             11.743296           \n", 
4891              "0.266667             6.781033             0.169228             11.743296           \n", 
4892              "0.400000             6.467623             0.168279             11.743296           \n", 
4893              "0.533333             6.333340             0.167876             11.743296           \n", 
4894              "0.666667             6.323238             0.167846             11.743296           \n", 
4895              "0.800000             6.005245             0.166902             11.743296           \n", 
4896              "0.933333             5.767052             0.166203             11.743296           \n", 
4897              "1.066667             5.476968             0.165361             11.743296           \n", 
4898              "1.200000             5.469949             0.165341             11.743296           \n", 
4899              "1.333333             5.295113             0.164838             11.743296           \n", 
4900              "1.466667             5.435648             0.165242             11.743296           \n", 
4901              "1.600000             5.410400             0.165169             11.743296           \n", 
4902              "1.733333             5.437554             0.165247             11.743296           \n", 
4903              "1.866667             5.176844             0.164501             11.743296           \n", 
4904              "2.000000             5.227232             0.164644             11.743296           \n", 
4905              "0.133333             11.530903            0.081928             18.789274           \n", 
4906              "0.266667             10.983094            0.081041             18.789274           \n", 
4907              "0.400000             10.512403            0.080294             18.789274           \n", 
4908              "0.533333             9.984805             0.079473             18.789274           \n", 
4909              "0.666667             9.573163             0.078845             18.789274           \n", 
4910              "0.800000             9.178810             0.078253             18.789274           \n", 
4911              "0.933333             8.935719             0.077893             18.789274           \n", 
4912              "1.066667             8.610147             0.077416             18.789274           \n", 
4913              "1.200000             8.353778             0.077045             18.789274           \n", 
4914              "1.333333             8.173729             0.076787             18.789274           \n", 
4915              "1.466667             8.091607             0.076670             18.789274           \n", 
4916              "1.600000             7.706420             0.076126             18.789274           \n", 
4917              "1.733333             7.709125             0.076129             18.789274           \n", 
4918              "1.866667             7.610856             0.075992             18.789274           \n", 
4919              "2.000000             7.552584             0.075911             18.789274           \n", 
4920          ] 
4921   
4922          # Check the batch file. 
4923          print("\nChecking the batch file.") 
4924          file = open("%s%sbatch_run.sh" % (ds.tmpdir, sep)) 
4925          lines = file.readlines() 
4926          file.close() 
4927          for i in range(len(lines)): 
4928              self.assertEqual(batch_file[i], lines[i]) 
4929   
4930          # Check spin :70@N. 
4931          print("\nChecking the spin :70@N input file.") 
4932          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_70_N')) 
4933          lines = file.readlines() 
4934          file.close() 
4935          for i in range(len(spin1)): 
4936              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
4937          for i in range(len(lines)): 
4938              self.assertEqual(spin1[i], lines[i]) 
4939   
4940          # Check spin :71@N. 
4941          print("\nChecking the spin :71@N input file.") 
4942          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_71_N')) 
4943          lines = file.readlines() 
4944          file.close() 
4945          for i in range(len(lines)): 
4946              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
4947          for i in range(len(spin2)): 
4948              self.assertEqual(spin2[i], lines[i]) 
4949   
4950   
4951 -    def test_korzhnev_2005_15n_dq_data(self): 
4952          """Optimisation of the Korzhnev et al., 2005 15N DQ CPMG data using the 'NS MMQ 2-site' model. 
4953   
4954          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
4955   
4956          Here only the 15N DQ data will be optimised.  The values found by cpmg_fit using just this data are: 
4957   
4958              - r2 = {'500': 9.487269007171426, '600': 11.718267257562591, '800': 13.624551743116887}, 
4959              - pA = 0.965402506690231, 
4960              - dw = 0.805197170133360, 
4961              - dwH = -0.595536627771890, 
4962              - kex = 569.003663067619868, 
4963              - chi2 = 9.297671357952812. 
4964          """ 
4965   
4966          # Base data setup. 
4967          self.setup_korzhnev_2005_data(data_list=['DQ']) 
4968   
4969          # Alias the spin. 
4970          spin = return_spin(":9@N") 
4971   
4972          # The R20 keys. 
4973          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
4974          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
4975          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
4976   
4977          # Set the initial parameter values. 
4978          spin.r2 = {r20_key1: 9.48527908326952, r20_key2: 11.7135951595536, r20_key3: 13.6153887849344} 
4979          spin.pA = 0.965638501551899 
4980          spin.dw = 2.8537583461577 
4981          spin.dwH = -0.387633062766635 
4982          spin.kex = 573.704033851592 
4983   
4984          # Low precision optimisation. 
4985          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
4986   
4987          # Monte Carlo simulations. 
4988          self.interpreter.monte_carlo.setup(number=2) 
4989          self.interpreter.monte_carlo.create_data(method='back_calc') 
4990          self.interpreter.monte_carlo.initial_values() 
4991          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
4992          self.interpreter.monte_carlo.error_analysis() 
4993   
4994          # Plot the dispersion curves. 
4995          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
4996   
4997          # Save the results. 
4998          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
4999   
5000          # Printout. 
5001          print("\n\nOptimised parameters:\n") 
5002          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5003          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5004          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5005          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5006          print("%-20s %20.15g" % ("pA", spin.pA)) 
5007          print("%-20s %20.15g" % ("dw", spin.dw)) 
5008          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5009          print("%-20s %20.15g" % ("kex", spin.kex)) 
5010          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5011   
5012          # Checks for residue :9. 
5013          self.assertAlmostEqual(spin.r2[r20_key1], 9.4870656457415, 2) 
5014          self.assertAlmostEqual(spin.r2[r20_key2], 11.7183291788929, 2) 
5015          self.assertAlmostEqual(spin.r2[r20_key3], 13.6241729933153, 2) 
5016          self.assertAlmostEqual(spin.pA, 0.965405468217295, 4) 
5017          self.assertAlmostEqual(spin.dw, 2.76835528427355, 1) 
5018          self.assertAlmostEqual(spin.dwH, -0.396489341086363, 2) 
5019          self.assertAlmostEqual(spin.kex/1000, 569.06937047601/1000, 3) 
5020          self.assertAlmostEqual(spin.chi2, 9.29767487125257, 2) 
5021   
5022   
5023 -    def test_korzhnev_2005_15n_mq_data(self): 
5024          """Optimisation of the Korzhnev et al., 2005 15N MQ CPMG data using the 'NS MMQ 2-site' model. 
5025   
5026          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5027   
5028          Here only the 15N MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5029   
5030              - r2 = {'500': 5.993083514798655, '600': 6.622184438384841, '800': 8.640765919352019}, 
5031              - pA = 0.930027999814003, 
5032              - dw = 4.338620619954370, 
5033              - dwH = -0.274250775560818, 
5034              - kex = 344.613362916544475, 
5035              - chi2 = 10.367733168217050. 
5036          """ 
5037   
5038          # Base data setup. 
5039          self.setup_korzhnev_2005_data(data_list=['MQ']) 
5040   
5041          # Alias the spin. 
5042          spin = return_spin(":9@N") 
5043   
5044          # The R20 keys. 
5045          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5046          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5047          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5048   
5049          # Set the initial parameter values. 
5050          spin.r2 = {r20_key1: 6.02016436619016, r20_key2: 6.65421500772308, r20_key3: 8.6729591487622} 
5051          spin.pA = 0.930083249288083 
5052          spin.dw = 4.33890689462363 
5053          spin.dwH = -0.274316585638047 
5054          spin.kex = 344.329651956132 
5055   
5056          # Low precision optimisation. 
5057          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5058   
5059          # Monte Carlo simulations. 
5060          self.interpreter.monte_carlo.setup(number=2) 
5061          self.interpreter.monte_carlo.create_data(method='back_calc') 
5062          self.interpreter.monte_carlo.initial_values() 
5063          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5064          self.interpreter.monte_carlo.error_analysis() 
5065   
5066          # Plot the dispersion curves. 
5067          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5068   
5069          # Save the results. 
5070          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5071   
5072          # Printout. 
5073          print("\n\nOptimised parameters:\n") 
5074          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5075          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5076          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5077          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5078          print("%-20s %20.15g" % ("pA", spin.pA)) 
5079          print("%-20s %20.15g" % ("dw", spin.dw)) 
5080          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5081          print("%-20s %20.15g" % ("kex", spin.kex)) 
5082          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5083   
5084          # Checks for residue :9. 
5085          self.assertAlmostEqual(spin.r2[r20_key1], 5.99503641023038, 1) 
5086          self.assertAlmostEqual(spin.r2[r20_key2], 6.62432897608527, 1) 
5087          self.assertAlmostEqual(spin.r2[r20_key3], 8.64278915809492, 1) 
5088          self.assertAlmostEqual(spin.pA, 0.930036474040713, 3) 
5089          self.assertAlmostEqual(spin.dw, 4.33848403058432, 2) 
5090          self.assertAlmostEqual(spin.dwH, -0.274246558825267, 3) 
5091          self.assertAlmostEqual(spin.kex/1000, 344.626563267384/1000, 3) 
5092          self.assertAlmostEqual(spin.chi2, 10.3677362372789, 2) 
5093   
5094   
5095 -    def test_korzhnev_2005_15n_sq_data(self): 
5096          """Optimisation of the Korzhnev et al., 2005 15N SQ CPMG data using the 'NS MMQ 2-site' model. 
5097   
5098          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5099   
5100          Here only the 15N SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5101   
5102              - r2 = {'500': 8.335037972570017, '600': 8.761366016417508, '800': 10.225001019091822}, 
5103              - pA = 0.950003458294991, 
5104              - dw = 4.358402855315123, 
5105              - kex = 429.906473361926999, 
5106              - chi2 = 17.393331915567252. 
5107          """ 
5108   
5109          # Base data setup. 
5110          self.setup_korzhnev_2005_data(data_list=['SQ']) 
5111   
5112          # Alias the spin. 
5113          spin = return_spin(":9@N") 
5114   
5115          # The R20 keys. 
5116          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5117          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5118          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5119   
5120          # Set the initial parameter values. 
5121          spin.r2 = {r20_key1: 8.334232330326190, r20_key2: 8.756773997879968, r20_key3: 10.219320492033058} 
5122          spin.pA = 0.950310172115387 
5123          spin.dw = 4.356737157889636 
5124          spin.kex = 433.176323890829849 
5125   
5126          # Low precision optimisation. 
5127          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5128   
5129          # Monte Carlo simulations. 
5130          self.interpreter.monte_carlo.setup(number=2) 
5131          self.interpreter.monte_carlo.create_data(method='back_calc') 
5132          self.interpreter.monte_carlo.initial_values() 
5133          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5134          self.interpreter.monte_carlo.error_analysis() 
5135   
5136          # Plot the dispersion curves. 
5137          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5138   
5139          # Save the results. 
5140          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5141   
5142          # Printout. 
5143          print("\n\nOptimised parameters:\n") 
5144          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5145          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5146          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5147          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5148          print("%-20s %20.15g" % ("pA", spin.pA)) 
5149          print("%-20s %20.15g" % ("dw", spin.dw)) 
5150          print("%-20s %20.15g" % ("kex", spin.kex)) 
5151          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5152   
5153          # Checks for residue :9. 
5154          self.assertAlmostEqual(spin.r2[r20_key1], 8.33499994313902, 2) 
5155          self.assertAlmostEqual(spin.r2[r20_key2], 8.76118738798082, 2) 
5156          self.assertAlmostEqual(spin.r2[r20_key3], 10.2250821829928, 1) 
5157          self.assertAlmostEqual(spin.pA, 0.950000281516303, 3) 
5158          self.assertAlmostEqual(spin.dw, 4.35845318983581, 2) 
5159          self.assertAlmostEqual(spin.kex/1000, 429.874510184149/1000, 2) 
5160          self.assertAlmostEqual(spin.chi2, 17.3933357984425, 1) 
5161   
5162   
5163 -    def test_korzhnev_2005_15n_zq_data(self): 
5164          """Optimisation of the Korzhnev et al., 2005 15N ZQ CPMG data using the 'NS MMQ 2-site' model. 
5165   
5166          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5167   
5168          Here only the 15N ZQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5169   
5170              - r2 = {'500': 5.909812628572937, '600': 6.663690132557320, '800': 6.787171647689906}, 
5171              - pA = 0.942452612380140, 
5172              - dw = 0.858972784230892, 
5173              - dwH = 0.087155962730608, 
5174              - kex = 373.219151384798920, 
5175              - chi2 = 23.863208106025152. 
5176          """ 
5177   
5178          # Base data setup. 
5179          self.setup_korzhnev_2005_data(data_list=['ZQ']) 
5180   
5181          # Alias the spin. 
5182          spin = return_spin(":9@N") 
5183   
5184          # The R20 keys. 
5185          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5186          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5187          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5188   
5189          # Set the initial parameter values. 
5190          spin.r2 = {r20_key1: 5.91033272691614, r20_key2: 6.66368695342258, r20_key3: 6.78922219135537} 
5191          spin.pA = 0.942457332074014 
5192          spin.dw = 0.850592422908884 
5193          spin.dwH = 0.0881272284455416 
5194          spin.kex = 372.745483351305 
5195   
5196          # Low precision optimisation. 
5197          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5198   
5199          # Monte Carlo simulations. 
5200          self.interpreter.monte_carlo.setup(number=2) 
5201          self.interpreter.monte_carlo.create_data(method='back_calc') 
5202          self.interpreter.monte_carlo.initial_values() 
5203          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5204          self.interpreter.monte_carlo.error_analysis() 
5205   
5206          # Plot the dispersion curves. 
5207          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5208   
5209          # Save the results. 
5210          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5211   
5212          # Printout. 
5213          print("\n\nOptimised parameters:\n") 
5214          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5215          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5216          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5217          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5218          print("%-20s %20.15g" % ("pA", spin.pA)) 
5219          print("%-20s %20.15g" % ("dw", spin.dw)) 
5220          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5221          print("%-20s %20.15g" % ("kex", spin.kex)) 
5222          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5223   
5224          # Checks for residue :9. 
5225          self.assertAlmostEqual(spin.r2[r20_key1], 5.9098385837035, 2) 
5226          self.assertAlmostEqual(spin.r2[r20_key2], 6.66377885876553, 2) 
5227          self.assertAlmostEqual(spin.r2[r20_key3], 6.78717432941353, 2) 
5228          self.assertAlmostEqual(spin.pA, 0.942457141344462, 4) 
5229          self.assertAlmostEqual(spin.dw, 0.84442055695814, 1) 
5230          self.assertAlmostEqual(spin.dwH, 0.0886367674566058, 2) 
5231          self.assertAlmostEqual(spin.kex/1000, 373.243053643367/1000, 3) 
5232          self.assertAlmostEqual(spin.chi2, 23.863211604121, 1) 
5233   
5234   
5235 -    def test_korzhnev_2005_1h_mq_data(self): 
5236          """Optimisation of the Korzhnev et al., 2005 1H MQ CPMG data using the 'NS MMQ 2-site' model. 
5237   
5238          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5239   
5240          Here only the 1H MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5241   
5242              - r2 = {'500': -0.000016676911302, '600': 0.036594127620440, '800': 2.131014839635728}, 
5243              - pA = 0.936911090448340, 
5244              - dw = 4.325314846914845, 
5245              - dwH = -0.213870168665628, 
5246              - kex = 487.361914835074117, 
5247              - chi2 = 14.870371897291138. 
5248          """ 
5249   
5250          # Base data setup. 
5251          self.setup_korzhnev_2005_data(data_list=['1H MQ']) 
5252   
5253          # Alias the spin. 
5254          spin = return_spin(":9@N") 
5255   
5256          # The R20 keys. 
5257          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5258          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5259          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5260   
5261          # Set the initial parameter values. 
5262          spin.r2 = {r20_key1: 0.000022585022901, r20_key2: 0.039223196112941, r20_key3: 2.136576686700357} 
5263          spin.pA = 0.936884348941701 
5264          spin.dw = 4.326454531583964 
5265          spin.dwH = -0.214026093221782 
5266          spin.kex = 487.043592705469223 
5267   
5268          # Low precision optimisation. 
5269          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=100) 
5270   
5271          # Monte Carlo simulations. 
5272          self.interpreter.monte_carlo.setup(number=2) 
5273          self.interpreter.monte_carlo.create_data(method='back_calc') 
5274          self.interpreter.monte_carlo.initial_values() 
5275          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5276          self.interpreter.monte_carlo.error_analysis() 
5277   
5278          # Plot the dispersion curves. 
5279          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5280   
5281          # Save the results. 
5282          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5283   
5284          # Printout. 
5285          print("\n\nOptimised parameters:\n") 
5286          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5287          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5288          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5289          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5290          print("%-20s %20.15g" % ("pA", spin.pA)) 
5291          print("%-20s %20.15g" % ("dw", spin.dw)) 
5292          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5293          print("%-20s %20.15g" % ("kex", spin.kex)) 
5294          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5295   
5296          # Checks for residue :9. 
5297          self.assertAlmostEqual(spin.r2[r20_key1], 2.48493199969936e-05, 4) 
5298          self.assertAlmostEqual(spin.r2[r20_key2], 0.0382382195911849, 2) 
5299          self.assertAlmostEqual(spin.r2[r20_key3], 2.13397221524655, 2) 
5300          self.assertAlmostEqual(spin.pA, 0.936879359956996, 4) 
5301          self.assertAlmostEqual(spin.dw, 4.32573362253701, 2) 
5302          self.assertAlmostEqual(spin.dwH, -0.213951762275293, 2) 
5303          self.assertAlmostEqual(spin.kex/1000, 487.021196851596/1000, 4) 
5304          self.assertAlmostEqual(spin.chi2, 14.8704048958378, 2) 
5305   
5306   
5307 -    def test_korzhnev_2005_1h_sq_data(self): 
5308          """Optimisation of the Korzhnev et al., 2005 1H SQ CPMG data using the 'NS MMQ 2-site' model. 
5309   
5310          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5311   
5312          Here only the 1H SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5313   
5314              - r2 = {'500': 6.691697587650816, '600': 6.998915158708793, '800': 5.519267837559072}, 
5315              - pA = 0.946949480545876, 
5316              - dwH = -0.265279672133308, 
5317              - kex = 406.548178869750700, 
5318              - chi2 = 50.400680290545026. 
5319          """ 
5320   
5321          # Base data setup. 
5322          self.setup_korzhnev_2005_data(data_list=['1H SQ']) 
5323   
5324          # Alias the spin. 
5325          spin = return_spin(":9@N") 
5326   
5327          # The R20 keys. 
5328          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5329          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5330          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5331   
5332          # Set the initial parameter values. 
5333          spin.r2 = {r20_key1: 6.69107911078939, r20_key2: 6.99888898689085, r20_key3: 5.52012880268077} 
5334          spin.pA = 0.946990967372467 
5335          spin.dwH = -0.265308128403529 
5336          spin.kex = 406.843250675648 
5337   
5338          # Low precision optimisation. 
5339          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5340   
5341          # Monte Carlo simulations. 
5342          self.interpreter.monte_carlo.setup(number=2) 
5343          self.interpreter.monte_carlo.create_data(method='back_calc') 
5344          self.interpreter.monte_carlo.initial_values() 
5345          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5346          self.interpreter.monte_carlo.error_analysis() 
5347   
5348          # Plot the dispersion curves. 
5349          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5350   
5351          # Save the results. 
5352          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5353   
5354          # Printout. 
5355          print("\n\nOptimised parameters:\n") 
5356          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5357          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5358          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5359          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5360          print("%-20s %20.15g" % ("pA", spin.pA)) 
5361          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5362          print("%-20s %20.15g" % ("kex", spin.kex)) 
5363          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5364   
5365          # Checks for residue :9. 
5366          self.assertAlmostEqual(spin.r2[r20_key1], 6.69168251154302, 2) 
5367          self.assertAlmostEqual(spin.r2[r20_key2], 6.99900388754043, 2) 
5368          self.assertAlmostEqual(spin.r2[r20_key3], 5.51921590064843, 2) 
5369          self.assertAlmostEqual(spin.pA, 0.946951877648819, 4) 
5370          self.assertAlmostEqual(spin.dwH, -0.265280175525516, 3) 
5371          self.assertAlmostEqual(spin.kex/1000, 406.566453278183/1000, 2) 
5372          self.assertAlmostEqual(spin.chi2, 50.4006836222044, 1) 
5373   
5374   
5375 -    def test_korzhnev_2005_all_data(self): 
5376          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5377   
5378          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5379   
5380          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5381   
5382              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5383                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5384                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5385                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5386                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5387                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5388              - pA = 0.943125351763911, 
5389              - dw = 4.421827493809807, 
5390              - dwH = -0.272637034755752, 
5391              - kex = 360.609744568697238, 
5392              - chi2 = 162.589570340050813. 
5393          """ 
5394   
5395          # Base data setup. 
5396          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5397   
5398          # Alias the spin. 
5399          spin = return_spin(":9@N") 
5400   
5401          # The R20 keys. 
5402          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5403          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5404          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5405          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5406          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5407          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5408          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5409          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5410          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5411          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5412          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5413          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5414          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5415          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5416          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5417          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5418          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5419          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5420   
5421          # Set the initial parameter values. 
5422          spin.r2 = { 
5423              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5424              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5425              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5426              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5427              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5428              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5429          } 
5430          spin.pA = 0.943129019477673 
5431          spin.dw = 4.42209952545181 
5432          spin.dwH = -0.27258970590969 
5433          spin.kex = 360.516132791038 
5434   
5435          # Low precision optimisation. 
5436          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=10) 
5437   
5438          # Monte Carlo simulations. 
5439          self.interpreter.monte_carlo.setup(number=2) 
5440          self.interpreter.monte_carlo.create_data(method='back_calc') 
5441          self.interpreter.monte_carlo.initial_values() 
5442          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5443          self.interpreter.monte_carlo.error_analysis() 
5444   
5445          # Plot the dispersion curves. 
5446          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5447   
5448          # Save the results. 
5449          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5450   
5451          # Printout. 
5452          print("\n\nOptimised parameters:\n") 
5453          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5454          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5455          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5456          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5457          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5458          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5459          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5460          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5461          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5462          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5463          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5464          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5465          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5466          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5467          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5468          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5469          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5470          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5471          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5472          print("%-20s %20.15g" % ("pA", spin.pA)) 
5473          print("%-20s %20.15g" % ("dw", spin.dw)) 
5474          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5475          print("%-20s %20.15g" % ("kex", spin.kex)) 
5476          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5477   
5478          # Checks for residue :9. 
5479          self.assertAlmostEqual(spin.r2[r20_key1],  6.67288025927458, 4) 
5480          self.assertAlmostEqual(spin.r2[r20_key2],  6.98951408255098, 4) 
5481          self.assertAlmostEqual(spin.r2[r20_key3],  5.52959273852704, 4) 
5482          self.assertAlmostEqual(spin.r2[r20_key4],  8.39471048876782, 4) 
5483          self.assertAlmostEqual(spin.r2[r20_key5],  8.89290699178799, 4) 
5484          self.assertAlmostEqual(spin.r2[r20_key6],  10.4077068723693, 4) 
5485          self.assertAlmostEqual(spin.r2[r20_key7],  5.93611174376373, 4) 
5486          self.assertAlmostEqual(spin.r2[r20_key8],  6.71735669582514, 4) 
5487          self.assertAlmostEqual(spin.r2[r20_key9],  6.83835225518265, 4) 
5488          self.assertAlmostEqual(spin.r2[r20_key10], 8.59615074668922, 4) 
5489          self.assertAlmostEqual(spin.r2[r20_key11], 10.6512137889291, 4) 
5490          self.assertAlmostEqual(spin.r2[r20_key12], 12.5710822919109, 4) 
5491          self.assertAlmostEqual(spin.r2[r20_key13], 7.85956711501608, 4) 
5492          self.assertAlmostEqual(spin.r2[r20_key14], 8.41891642907918, 4) 
5493          self.assertAlmostEqual(spin.r2[r20_key15], 11.2362089223038, 4) 
5494          self.assertAlmostEqual(spin.r2[r20_key16], 9.1965486378935, 4) 
5495          self.assertAlmostEqual(spin.r2[r20_key17], 9.86031627358462, 4) 
5496          self.assertAlmostEqual(spin.r2[r20_key18], 11.9752375592575, 4) 
5497          self.assertAlmostEqual(spin.pA, 0.943129019477673, 4) 
5498          self.assertAlmostEqual(spin.dw, 4.42209952545181, 4) 
5499          self.assertAlmostEqual(spin.dwH, -0.27258970590969, 4) 
5500          self.assertAlmostEqual(spin.kex/1000, 360.516132791038/1000, 4) 
5501          self.assertAlmostEqual(spin.chi2/1000, 162.596331278669/1000, 3) 
5502   
5503   
5504 -    def test_korzhnev_2005_all_data_disp_speed_bug(self): 
5505          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5506   
5507          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5508   
5509          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5510   
5511              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5512                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5513                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5514                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5515                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5516                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5517              - pA = 0.943125351763911, 
5518              - dw = 4.421827493809807, 
5519              - dwH = -0.272637034755752, 
5520              - kex = 360.609744568697238, 
5521              - chi2 = 162.589570340050813. 
5522          """ 
5523   
5524          # Base data setup. 
5525          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5526   
5527          # Alias the spin. 
5528          spin = return_spin(":9@N") 
5529   
5530          # The R20 keys. 
5531          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5532          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5533          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5534          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5535          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5536          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5537          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5538          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5539          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5540          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5541          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5542          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5543          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5544          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5545          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5546          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5547          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5548          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5549   
5550          # Set the initial parameter values. 
5551          spin.r2 = { 
5552              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5553              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5554              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5555              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5556              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5557              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5558          } 
5559          spin.pA = 0.943129019477673 
5560          spin.dw = 4.42209952545181 
5561          spin.dwH = -0.27258970590969 
5562          spin.kex = 360.516132791038 
5563   
5564          # Calc the chi2 values at these parameters. 
5565          self.interpreter.minimise.calculate(verbosity=1) 
5566   
5567          # Printout. 
5568          print("\n\nOptimised parameters:\n") 
5569          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5570          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5571          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5572          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5573          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5574          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5575          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5576          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5577          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5578          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5579          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5580          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5581          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5582          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5583          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5584          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5585          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5586          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5587          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5588          print("%-20s %20.15g" % ("pA", spin.pA)) 
5589          print("%-20s %20.15g" % ("dw", spin.dw)) 
5590          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5591          print("%-20s %20.15g" % ("kex", spin.kex)) 
5592          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5593   
5594          # Checks for residue :9. 
5595          self.assertAlmostEqual(spin.chi2/1000, 162.511988511609/1000, 3) 
5596   
5597   
5598 -    def test_kteilum_fmpoulsen_makke_check_graphs(self): 
5599          """Check of all possible dispersion graphs from optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5600   
5601          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5602   
5603          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5604   
5605            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5606            - 0.483 0.89623903 2.4503699912708878 
5607            - 0.545 1.1694838 
5608            - 0.545 1.1761503 
5609            - 0.622 1.294 
5610            - 0.669 1.5176493 
5611            - 0.722 1.6238791 
5612            - 0.813 1.9395758 
5613            - 1.011 2.3558415 10.547000429321157 
5614          """ 
5615   
5616          # Base data setup. 
5617          model = 'TSMFK01' 
5618          expfolder = "acbp_cpmg_disp_048MGuHCl_40C_041223" 
5619          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model=model, expfolder=expfolder) 
5620   
5621          # Alias the spins. 
5622          res61L = cdp.mol[0].res[0].spin[0] 
5623   
5624          # The R20 keys. 
5625          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5626   
5627          # Set the initial parameter values. 
5628          res61L.r2a = {r20_key1: 8.0} 
5629          res61L.dw = 6.5 
5630          res61L.k_AB = 2.5 
5631   
5632          # Low precision optimisation. 
5633          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5634   
5635          # Start testing all possible combinations of graphs. 
5636          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
5637          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
5638          interpolate_types = [INTERPOLATE_DISP] 
5639   
5640          # Write to temp folder. 
5641          result_dir_name = ds.tmpdir 
5642          result_folders = [model] 
5643          spin_id = ":61@N" 
5644   
5645          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
5646          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder+sep+'check_graphs' 
5647   
5648          for result_folder in result_folders: 
5649              for y_axis in y_axis_types: 
5650                  for x_axis in x_axis_types: 
5651                      for interpolate in interpolate_types: 
5652                          # Determine file name: 
5653                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
5654   
5655                          # Make the file name. 
5656                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
5657   
5658                          # Write the curves. 
5659                          dir = result_dir_name+sep+result_folder 
5660                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
5661                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
5662   
5663                          # Get the file path. 
5664                          file_path = get_file_path(file_name, dir) 
5665   
5666                          # Test the plot file exists. 
5667                          print("Testing file access to graph: %s"%file_path) 
5668                          self.assert_(access(file_path, F_OK)) 
5669   
5670                          # Now open, and compare content, line by line. 
5671                          file_prod = open(file_path) 
5672                          lines_prod = file_prod.readlines() 
5673                          file_prod.close() 
5674   
5675                          # Define file to compare against. 
5676                          dir_comp = data_path+sep+result_folder 
5677                          file_path_comp = get_file_path(file_name, dir_comp) 
5678                          file_comp = open(file_path_comp) 
5679                          lines_comp = file_comp.readlines() 
5680                          file_comp.close() 
5681   
5682                          ## Assert number of lines is equal. 
5683                          self.assertEqual(len(lines_prod), len(lines_comp)) 
5684                          for j in range(len(lines_prod)): 
5685                              # Make the string test 
5686                              first_char = lines_prod[j][0] 
5687                              if first_char in ["@", "&"]: 
5688                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
5689                              else: 
5690                                  # Split string in x, y, error. 
5691                                  # The error would change per run. 
5692                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
5693                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
5694                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
5695                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
5696                                  self.assertAlmostEqual(float(y_prod_err), float(y_comp_err)) 
5697   
5698   
5699 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72(self): 
5700          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5701   
5702          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5703          """ 
5704   
5705          # Base data setup. 
5706          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5707   
5708          # Alias the spins. 
5709          res61L = cdp.mol[0].res[0].spin[0] 
5710   
5711          # The R20 keys. 
5712          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5713   
5714          # Set the initial parameter values. 
5715          res61L.r2 = {r20_key1: 8.0} 
5716          res61L.pA = 0.9 
5717          res61L.dw = 6.0 
5718          res61L.kex = 600.0 
5719   
5720          # Low precision optimisation. 
5721          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5722   
5723          # Printout. 
5724          print("\n\nOptimised parameters:\n") 
5725          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5726          print("%-20s %20.15g" % ("R2 (600 MHz)", res61L.r2[r20_key1])) 
5727          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5728          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5729          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5730          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5731   
5732          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5733          self.assertAlmostEqual(res61L.r2[r20_key1], 8.69277980194016, 4) 
5734          self.assertAlmostEqual(res61L.pA, 0.9943781590842946, 5) 
5735          self.assertAlmostEqual(res61L.dw, 6.389453131263374, 3) 
5736          self.assertAlmostEqual(res61L.kex, 609.262167216419, 0) 
5737          self.assertAlmostEqual(res61L.chi2, 65.99987828889657, 5) 
5738   
5739          # Test the conversion to k_AB from kex and pA. 
5740          self.assertEqual(res61L.k_AB, res61L.kex * (1.0 - res61L.pA)) 
5741   
5742          # Test the conversion to k_BA from kex and pA. 
5743          self.assertEqual(res61L.k_BA, res61L.kex * res61L.pA) 
5744   
5745   
5746 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72_full(self): 
5747          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5748   
5749          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5750          """ 
5751   
5752          # Base data setup. 
5753          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72 full', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5754   
5755          # Alias the spins. 
5756          res61L = cdp.mol[0].res[0].spin[0] 
5757   
5758          # The R20 keys. 
5759          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5760   
5761          # Set the initial parameter values. 
5762          res61L.r2a = {r20_key1: 8.0} 
5763          res61L.r2b = {r20_key1: 105.0} 
5764          res61L.pA = 0.9 
5765          res61L.dw = 6.0 
5766          res61L.kex = 500.0 
5767   
5768          # Low precision optimisation. 
5769          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5770   
5771          # Printout. 
5772          print("\n\nOptimised parameters:\n") 
5773          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5774          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5775          print("%-20s %20.15g" % ("R2B (600 MHz)", res61L.r2b[r20_key1])) 
5776          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5777          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5778          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5779          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5780   
5781          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5782          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.044428899438309, 0) 
5783          self.assertAlmostEqual(res61L.r2b[r20_key1], 105.11894506392449, -2) 
5784          self.assertAlmostEqual(res61L.pA, 0.992066883657578, 2) 
5785          self.assertAlmostEqual(res61L.dw, 6.389453586338883, 3) 
5786          self.assertAlmostEqual(res61L.kex, 513.483608742063, -2) 
5787          self.assertAlmostEqual(res61L.chi2, 65.99987828890289, 5) 
5788   
5789   
5790 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_tsmfk01(self): 
5791          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5792   
5793          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5794   
5795          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5796   
5797            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5798            - 0.483 0.89623903 2.4503699912708878 
5799            - 0.545 1.1694838 
5800            - 0.545 1.1761503 
5801            - 0.622 1.294 
5802            - 0.669 1.5176493 
5803            - 0.722 1.6238791 
5804            - 0.813 1.9395758 
5805            - 1.011 2.3558415 10.547000429321157 
5806          """ 
5807   
5808          # Base data setup. 
5809          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5810   
5811          # Alias the spins. 
5812          res61L = cdp.mol[0].res[0].spin[0] 
5813   
5814          # The R20 keys. 
5815          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5816   
5817          # Set the initial parameter values. 
5818          res61L.r2a = {r20_key1: 8.0} 
5819          res61L.dw = 6.5 
5820          res61L.k_AB = 2.5 
5821   
5822          # Low precision optimisation. 
5823          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5824   
5825          # Printout. 
5826          print("\n\nOptimised parameters:\n") 
5827          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5828          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5829          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5830          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5831          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5832   
5833          # Checks for residue :61. Reference values from paper 
5834   
5835          self.assertAlmostEqual(res61L.k_AB, 2.45, 1) 
5836   
5837   
5838 -    def test_kteilum_fmpoulsen_makke_cpmg_data_101m_guhcl_to_tsmfk01(self): 
5839          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5840   
5841          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 1.01 M GuHCl (guanidine hydrochloride). 
5842   
5843          The comparison is to Figure 2, which is for dataset with 1 M GuHCl.  The reported results are expected to be in rad.s^-1.  Conversion into relax stored values is preferably. 
5844   
5845          Representative 15N CPMG relaxation dispersion curve measured on the cross peaks from residue L61 in folded ACBP at pH 5.3, 1 M GuHCl, and 40C: 
5846   
5847            1. The dotted line represents a residue-specific fit of all parameters in Eq. 1: 
5848              - k_AB = 11.3 +/- 0.7 s^-1, 
5849              - dw = (2.45 +/- 0.09) * 10^3 s^-1, 
5850              - R2 = 8.0 +/- 0.5 s^-1. 
5851   
5852            2. The solid line represents a global fit of k_AB to all protein residues and a residue-specific fit of dw and R2.: 
5853              - k_AB = 10.55 +/- 0.08 s^-1, 
5854              - dw = (2.44 +/- 0.08) * 10^3 s^-1, 
5855              - R2 = 8.4 +/- 0.3 s^-1. 
5856   
5857          Conversion of paper results to relax results is performed by: 
5858   
5859            - dw(ppm) = dw(rad.s^-1) * 10^6 * 1/(2*pi) * (gyro1H/(gyro15N*spectrometer_freq)) = 2.45E3 * 1E6 / (2 * math.pi) * (26.7522212E7/(-2.7126E7 * 599.8908622E6)) = -6.41 ppm. 
5860   
5861          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl.  The precise values are: 
5862   
5863            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5864            - 0.483 0.89623903 2.4503699912708878 
5865            - 0.545 1.1694838 
5866            - 0.545 1.1761503 
5867            - 0.622 1.294 
5868            - 0.669 1.5176493 
5869            - 0.722 1.6238791 
5870            - 0.813 1.9395758 
5871            - 1.011 2.3558415 10.547000429321157 
5872          """ 
5873   
5874          # Base data setup. 
5875          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_101MGuHCl_40C_041223") 
5876   
5877          # Alias the spins. 
5878          res61L = cdp.mol[0].res[0].spin[0] 
5879   
5880          # The R20 keys. 
5881          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086270e6) 
5882   
5883          # Set the initial parameter values. 
5884          res61L.r2a = {r20_key1: 8.0} 
5885          res61L.dw = 6.5 
5886          res61L.k_AB = 11.0 
5887   
5888          # Low precision optimisation. 
5889          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5890   
5891          # Printout. 
5892          print("\n\nOptimised parameters:\n") 
5893          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5894          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5895          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5896          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5897          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5898   
5899          # Checks for residue :61. Reference values from paper 
5900   
5901          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.4, 0) 
5902          self.assertAlmostEqual(res61L.dw, 6.41, 0) 
5903          self.assertAlmostEqual(res61L.k_AB, 10.55, 0) 
5904   
5905   
5906 -    def test_lm63_3site_synthetic(self): 
5907          """Test the 'LM63 3-site' dispersion model using the pure noise-free synthetic data.""" 
5908   
5909          # The path to the data files. 
5910          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'lm63_3site' 
5911   
5912          # Load the state file. 
5913          self.interpreter.reset() 
5914          self.interpreter.state.load(data_path+sep+'r2eff_values') 
5915   
5916          # A new data pipe. 
5917          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='LM63 3-site', bundle_to='relax_disp') 
5918          self.interpreter.pipe.switch(pipe_name='LM63 3-site') 
5919   
5920          # Set up the model data. 
5921          self.interpreter.relax_disp.select_model(model='LM63 3-site') 
5922          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='LM63 3-site', param='r2eff') 
5923          self.interpreter.spin.isotope('15N') 
5924   
5925          # Alias the spins. 
5926          spin1 = return_spin(":1") 
5927          spin2 = return_spin(":2") 
5928   
5929          # The R20 keys. 
5930          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5931          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5932   
5933          # Manually set the parameter values. 
5934          spin1.r2 = {r20_key1: 12.0, r20_key2: 12.0} 
5935          spin1.phi_ex_B = 0.1 
5936          spin1.phi_ex_C = 0.5 
5937          spin1.kB = 1500.0 
5938          spin1.kC = 2500.0 
5939          spin2.r2 = {r20_key1: 15.0, r20_key2: 15.0} 
5940          spin2.phi_ex_B = 0.1 
5941          spin2.phi_ex_C = 0.5 
5942          spin2.kB = 1500.0 
5943          spin2.kC = 2500.0 
5944   
5945          # Low precision optimisation. 
5946          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5947   
5948          # Monte Carlo simulations. 
5949          self.interpreter.monte_carlo.setup(number=3) 
5950          self.interpreter.monte_carlo.create_data(method='back_calc') 
5951          self.interpreter.monte_carlo.initial_values() 
5952          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-2, grad_tol=None, max_iter=10, constraints=True, scaling=True, verbosity=1) 
5953          self.interpreter.monte_carlo.error_analysis() 
5954   
5955          # Save the results. 
5956          self.interpreter.results.write(file='devnull', compress_type=1, force=True) 
5957   
5958          # The model checks. 
5959          print("\n\nOptimised parameters:\n") 
5960          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
5961          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
5962          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
5963          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin1.phi_ex_B, spin2.phi_ex_B)) 
5964          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin1.phi_ex_C, spin2.phi_ex_C)) 
5965          print("%-20s %20.15g %20.15g" % ("kB", spin1.kB, spin2.kB)) 
5966          print("%-20s %20.15g %20.15g" % ("kC", spin1.kC, spin2.kC)) 
5967          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
5968          self.assertAlmostEqual(spin1.r2[r20_key1], 12.0, 2) 
5969          self.assertAlmostEqual(spin1.r2[r20_key2], 12.0, 2) 
5970          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
5971          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
5972          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
5973          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
5974          self.assertAlmostEqual(spin1.chi2, 0.0, 3) 
5975          self.assertAlmostEqual(spin2.r2[r20_key1], 15.0, 3) 
5976          self.assertAlmostEqual(spin2.r2[r20_key2], 15.0, 3) 
5977          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
5978          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
5979          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
5980          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
5981          self.assertAlmostEqual(spin2.chi2, 0.0, 3) 
5982   
5983   
5984 -    def test_m61_data_to_m61(self): 
5985          """Test the relaxation dispersion 'M61' model curve fitting to fixed time synthetic data.""" 
5986   
5987          # Fixed time variable. 
5988          ds.fixed = True 
5989   
5990          # Execute the script. 
5991          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
5992   
5993          # The original parameters. 
5994          i0 = [100000.0, 20000.0] 
5995          r1rho_prime = [2.25, 24.0] 
5996          pA = 0.7 
5997          kex = 1000.0 
5998          delta_omega = [1.0, 2.0] 
5999          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6000          phi_ex = [] 
6001          for i in range(2): 
6002              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6003          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6004   
6005          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6006          self.interpreter.pipe.switch('R2eff - relax_disp') 
6007          spin_index = 0 
6008          for spin, spin_id in spin_loop(return_id=True): 
6009              # Printout. 
6010              print("\nSpin %s." % spin_id) 
6011   
6012              # Check the fitted parameters. 
6013              for i in range(len(keys)): 
6014                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6015   
6016              # Increment the spin index. 
6017              spin_index += 1 
6018   
6019          # The R20 keys. 
6020          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6021   
6022          # Switch to the 'M61' model data pipe, then check for each spin. 
6023          self.interpreter.pipe.switch('M61 - relax_disp') 
6024          spin_index = 0 
6025          for spin, spin_id in spin_loop(return_id=True): 
6026              # Printout. 
6027              print("\nSpin %s." % spin_id) 
6028   
6029              # Check the fitted parameters. 
6030              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6031              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6032              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6033   
6034              # Increment the spin index. 
6035              spin_index += 1 
6036   
6037   
6038 -    def test_m61_exp_data_to_m61(self): 
6039          """Test the relaxation dispersion 'M61' model curve fitting to the full exponential synthetic data.""" 
6040   
6041          # Fixed time variable. 
6042          ds.fixed = False 
6043   
6044          # Single spin optimisation. 
6045          ds.single = True 
6046   
6047          # Execute the script. 
6048          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6049   
6050          # The original parameters. 
6051          i0 = [100000.0, 20000.0] 
6052          r1rho_prime = [2.25, 24.0] 
6053          pA = 0.7 
6054          kex = 1000.0 
6055          delta_omega = [1.0, 2.0] 
6056          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6057          phi_ex = [] 
6058          for i in range(2): 
6059              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6060          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6061   
6062          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6063          self.interpreter.pipe.switch('R2eff - relax_disp') 
6064          spin_index = 0 
6065          for spin, spin_id in spin_loop(return_id=True): 
6066              # Printout. 
6067              print("\nSpin %s." % spin_id) 
6068   
6069              # Check the fitted parameters. 
6070              for i in range(len(keys)): 
6071                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6072   
6073              # Increment the spin index. 
6074              spin_index += 1 
6075   
6076          # The R20 keys. 
6077          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6078   
6079          # Switch to the 'M61' model data pipe, then check for each spin. 
6080          self.interpreter.pipe.switch('M61 - relax_disp') 
6081          spin_index = 0 
6082          for spin, spin_id in spin_loop(return_id=True): 
6083              # Printout. 
6084              print("\nSpin %s." % spin_id) 
6085   
6086              # Check the fitted parameters. 
6087              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6088              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6089              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6090   
6091              # Increment the spin index. 
6092              spin_index += 1 
6093   
6094   
6095 -    def test_m61b_data_to_m61b(self): 
6096          """Test the relaxation dispersion 'M61 skew' model curve fitting to fixed time synthetic data.""" 
6097   
6098          # Execute the script. 
6099          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61b.py') 
6100   
6101          # The original parameters. 
6102          i0 = [100000.0, 20000.0] 
6103          r1rho_prime = [10.0, 24.0] 
6104          pA = 0.95 
6105          kex = 2000.0 
6106          delta_omega = [1.0, 2.0] 
6107   
6108          # The R20 keys. 
6109          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6110   
6111          # Switch to the 'M61 skew' model data pipe, then check for each spin. 
6112          self.interpreter.pipe.switch("%s - relax_disp" % MODEL_M61B) 
6113          spin_index = 0 
6114          for spin, spin_id in spin_loop(return_id=True): 
6115              # Printout. 
6116              print("\nSpin %s." % spin_id) 
6117   
6118              # Check the fitted parameters. 
6119              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6120              self.assertAlmostEqual(spin.pA, pA, 2) 
6121              self.assertAlmostEqual(spin.dw, dw[spin_index], 2) 
6122              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6123   
6124              # Increment the spin index. 
6125              spin_index += 1 
6126   
6127   
6128 -    def test_model_nesting_and_param(self): 
6129          """Test that all models which can nest, have all their parameters converted.""" 
6130   
6131          # Set the experiment type. 
6132          cdp.exp_type_list = EXP_TYPE_LIST 
6133   
6134          # Get info for all models. 
6135          all_models_info = models_info(models=MODEL_LIST_FULL) 
6136   
6137          # Loop over all models. 
6138          print("Printing the listed of nested models for each model.") 
6139          print("#########################################") 
6140          for model_info in all_models_info: 
6141              print("%s"%model_info.model), 
6142              print("<-"), 
6143              nest_list = model_info.nest_list 
6144              if nest_list == None: 
6145                  nest_list = ["None"] 
6146              print(', '.join(map(str, nest_list))) 
6147   
6148              # Skip if there is no model to nest from. 
6149              if nest_list == ["None"]: 
6150                  continue 
6151   
6152              # Assign params to variable. 
6153              model_params = model_info.params 
6154   
6155              # Now loop over the nested models. 
6156              for nested_model in nest_list: 
6157                  # Get the params for the nested model. 
6158                  nested_model_params = MODEL_PARAMS[nested_model] 
6159   
6160                  # Get the dictionary of parameter conversion. 
6161                  par_dic = nesting_param(model_params=model_params, nested_model_params=nested_model_params) 
6162   
6163                  # Test the number of elements in the dictionary. 
6164                  self.assertEqual(len(par_dic), len(model_params)) 
6165   
6166                  # Loop over dictionary. 
6167                  for param in par_dic: 
6168                          if param != par_dic[param]: 
6169                              print("Model:'%s', Nested model:'%s', Copying '%s' to '%s'." % (model_info.model, nested_model, par_dic[param], param)) 
6170                          self.assertNotEqual(par_dic[param], None) 
6171   
6172   
6173 -    def test_ns_mmq_3site(self): 
6174          """Compare the 'NS MMQ 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6175   
6176          # Execute the script. 
6177          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site.py') 
6178   
6179          # Check the chi-squared value. 
6180          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6181   
6182   
6183 -    def test_ns_mmq_3site_linear(self): 
6184          """Compare the 'NS MMQ 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6185   
6186          # Execute the script. 
6187          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site_linear.py') 
6188   
6189          # Check the chi-squared value. 
6190          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6191   
6192   
6193 -    def test_ns_r1rho_3site(self): 
6194          """Compare the 'NS R1rho 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6195   
6196          # Execute the script. 
6197          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site.py') 
6198   
6199          # Check the chi-squared value. 
6200          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 136.13141468674999, 3) 
6201   
6202   
6203 -    def test_ns_r1rho_3site_linear(self): 
6204          """Compare the 'NS R1rho 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6205   
6206          # Execute the script. 
6207          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site_linear.py') 
6208   
6209          # Check the chi-squared value. 
6210          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 0.030959849811015544, 3) 
6211   
6212   
6213 -    def test_repeat_cpmg(self): 
6214          """Test the protocol for repeated dispersion analysis. The class: relax_disp_repeat_cpmg. 
6215   
6216          U{task #7826<https://gna.org/task/index.php?7826>}. Write an python class for the repeated analysis of dispersion data. 
6217          """ 
6218   
6219          # Reset. 
6220          self.interpreter.reset() 
6221   
6222          # Define base path to files. 
6223          base_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1' 
6224   
6225          # Setup dictionary with settings. 
6226          sdic = {} 
6227           
6228          # Spectrometer frqs in list. 
6229          sfrq_1 = 499.86214 
6230          sfrq_2 = 599.8908587 
6231          sfrqs = [sfrq_1, sfrq_2] 
6232           
6233          # Store in dictionary. 
6234          sdic['sfrqs'] = sfrqs 
6235           
6236          # Store unit for frq. 
6237          sdic['sfrq_unit'] = 'MHz' 
6238           
6239          # Store exp_type 
6240          sdic['exp_type'] = 'SQ CPMG' 
6241   
6242          # Store spin isotope 
6243          sdic['isotope'] = '15N' 
6244   
6245          # How intensity was measured. 
6246          sdic['int_method'] = 'height' 
6247   
6248          # Define the time for result directory. 
6249          sdic['time'] = '2014_09' 
6250   
6251          # Initialize frq dics. 
6252          for frq in sfrqs: 
6253              key = DIC_KEY_FORMAT % (frq) 
6254              sdic[key] = {} 
6255           
6256          # Set keys. 
6257          e_1 = DIC_KEY_FORMAT % (sfrq_1) 
6258          e_2 = DIC_KEY_FORMAT % (sfrq_2) 
6259           
6260          # Store time T2. 
6261          sdic[e_1]['time_T2'] = 0.04 
6262          sdic[e_2]['time_T2'] = 0.06 
6263           
6264          # Set ncyc. 
6265          ncyc_1 = array([20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0]) 
6266          ncyc_2 = array([28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 52, 18, 40, 6, 12, 0, 24, 14, 22]) 
6267   
6268          # Calculate the cpmg_frq and store. 
6269          sdic[e_1]['cpmg_frqs'] = ncyc_1 / sdic[e_1]['time_T2'] 
6270          sdic[e_2]['cpmg_frqs'] = ncyc_2 / sdic[e_2]['time_T2'] 
6271           
6272          # Define peak lists. 
6273          peaks_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files' 
6274          peaks_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files'  
6275          sdic[e_1]['peaks_folder'] = peaks_folder_1 
6276          sdic[e_2]['peaks_folder'] = peaks_folder_2 
6277           
6278          # Define folder to all rmsd files. 
6279          rmsd_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'ft2_data' 
6280          rmsd_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'ft2_data' 
6281          sdic[e_1]['rmsd_folder'] = rmsd_folder_1  
6282          sdic[e_2]['rmsd_folder'] = rmsd_folder_2 
6283   
6284          # Define temporary folder. 
6285          sdic['results_dir'] = self.tmpdir 
6286   
6287          # Setup class with data. 
6288          RDR =  Relax_disp_rep(sdic) 
6289   
6290          # Setup base information. 
6291          RDR.set_base_cpmg(method='FT', glob_ini=128) 
6292   
6293          methods = ['FT', 'MDD'] 
6294          #methods = ['FT'] 
6295   
6296          # Set the intensity. 
6297          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=False, set_rep=True) 
6298          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=True, set_rep=False) 
6299   
6300          # Try plot some intensity correlations. 
6301          if True: 
6302              selection = None 
6303   
6304              # Now make a spin selection. 
6305              int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128, 126], selection=selection) 
6306   
6307              # For mdd 
6308              int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6309   
6310              # Plot correlation of intensity 
6311              fig1 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6312              fig2 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6313              corr_data = [fig1, fig2] 
6314   
6315              write_stats = True 
6316              RDR.plot_int_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6317   
6318              # Open stat file. 
6319              if write_stats: 
6320                  for i, corr_data_i in enumerate(corr_data): 
6321                      data, methods, glob_inis = corr_data[i] 
6322                      data_x, data_y = data 
6323                      method_x, method_y = methods 
6324                      glob_ini_x, glob_ini_y = glob_inis 
6325                      x = data_x[str(glob_ini_x)]['peak_intensity_arr'] 
6326                      np = len(x) 
6327   
6328                      file_name_ini = 'int_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6329   
6330                      if selection == None: 
6331                          file_name = file_name_ini + '_all.txt' 
6332                      else: 
6333                          file_name = file_name_ini + '_sel.txt' 
6334                      path = RDR.results_dir 
6335                      data = extract_data(file=file_name, dir=path) 
6336   
6337                      # Loop over the lines. 
6338                      for i, data_i in enumerate(data): 
6339                          print(i, data_i) 
6340   
6341   
6342          # Try plot some intensity statistics. 
6343          if True: 
6344              # Collect r2eff values. 
6345              selections = [None, ':2,3'] 
6346              for selection in selections: 
6347                  int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128], selection=selection) 
6348                  int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6349   
6350                  # Get R2eff stats. 
6351                  int_stat_dic = RDR.get_int_stat_dic(list_int_dics=[int_ft_sel, int_mdd_sel], list_glob_ini=[128, 126]) 
6352   
6353                  ## Plot R2eff stats 
6354                  write_stats = True 
6355                  RDR.plot_int_stat(int_stat_dic=int_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126], show=False, write_stats=write_stats) 
6356   
6357                  # Open stat file. 
6358                  if write_stats: 
6359                      if selection == None: 
6360                          file_name = 'int_stat_all.txt' 
6361                      else: 
6362                          file_name = 'int_stat_sel.txt' 
6363                      path = RDR.results_dir 
6364                      data = extract_data(file=file_name, dir=path) 
6365   
6366                      # Loop over the lines. 
6367                      for i, data_i in enumerate(data): 
6368                          print(i, data_i) 
6369   
6370   
6371          # Try write some R2eff correlations. 
6372          if True: 
6373              selection = None 
6374              # Collect r2eff values. 
6375              r2eff_ft_all = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6376   
6377              # For all spins, mdd 
6378              r2eff_mdd_all = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6379   
6380              # Plot correlation of intensity 
6381              fig1 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 128]] 
6382              fig2 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 126]] 
6383              corr_data = [fig1, fig2] 
6384   
6385              write_stats = True 
6386              RDR.plot_r2eff_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6387   
6388              # Open stat file. 
6389              if write_stats: 
6390                  for i, corr_data_i in enumerate(corr_data): 
6391                      data, methods, glob_inis = corr_data[i] 
6392                      data_x, data_y = data 
6393                      method_x, method_y = methods 
6394                      glob_ini_x, glob_ini_y = glob_inis 
6395                      x = data_x[str(glob_ini_x)]['r2eff_arr'] 
6396                      np = len(x) 
6397   
6398                      file_name_ini = 'r2eff_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6399   
6400                      if selection == None: 
6401                          file_name = file_name_ini + '_all.txt' 
6402                      else: 
6403                          file_name = file_name_ini + '_sel.txt' 
6404                      path = RDR.results_dir 
6405                      data = extract_data(file=file_name, dir=path) 
6406   
6407                      # Loop over the lines. 
6408                      for i, data_i in enumerate(data): 
6409                          print(i, data_i) 
6410   
6411   
6412          # Try plot some R2eff statistics. 
6413          if True: 
6414              # Collect r2eff values. 
6415              selections = [None, ':2,3'] 
6416              for selection in selections: 
6417                  r2eff_ft_sel = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6418                  r2eff_mdd_sel = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6419   
6420                  # Get R2eff stats. 
6421                  r2eff_stat_dic = RDR.get_r2eff_stat_dic(list_r2eff_dics=[r2eff_ft_sel, r2eff_mdd_sel], list_glob_ini=[128, 126]) 
6422   
6423                  ## Plot R2eff stats 
6424                  write_stats = True 
6425                  RDR.plot_r2eff_stat(r2eff_stat_dic=r2eff_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6426   
6427                  # Open stat file. 
6428                  if write_stats: 
6429                      if selection == None: 
6430                          file_name = 'r2eff_stat_all.txt' 
6431                      else: 
6432                          file_name = 'r2eff_stat_sel.txt' 
6433                      path = RDR.results_dir 
6434                      data = extract_data(file=file_name, dir=path) 
6435   
6436                      # Loop over the lines. 
6437                      for i, data_i in enumerate(data): 
6438                          print(i, data_i) 
6439   
6440   
6441          # Do minimisation individual. 
6442          if True: 
6443              methods = ['FT', 'MDD'] 
6444              # Now calculate R2eff. 
6445              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6446   
6447              min_methods = [['FT'], ['MDD']] 
6448              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6449   
6450              #min_methods = [['FT']] 
6451              #min_list_glob_ini = [[128]] 
6452              #selection = ':2,3' 
6453              selection = None 
6454   
6455              for i, methods in enumerate(min_methods): 
6456                  list_glob_ini = min_list_glob_ini[i] 
6457   
6458                  if True: 
6459                      # First get data. 
6460                      if True: 
6461                          # First load all data. 
6462                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6463   
6464                      # Then set R20 
6465                      if True: 
6466                          # Set R20 from min R2eff in preparation for Grid search. 
6467                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, model_from=MODEL_R2EFF, analysis='grid_setup_ind', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6468   
6469                      # Check and print parameters. 
6470                      if True: 
6471                          # Print for pipe name 
6472                          method = methods[0] 
6473                          glob_ini = list_glob_ini[0] 
6474   
6475                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup_ind', glob_ini=glob_ini) 
6476                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6477   
6478                      # Then Grid search. 
6479                      if True: 
6480                          # Do Grid search. 
6481                          RDR.minimise_grid_search(inc=4, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6482   
6483                  # Then Minimise. 
6484                  if True: 
6485                      # Minimise 
6486                      RDR.opt_max_iterations = int(1e2) 
6487                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min_ind', analysis_from='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6488   
6489                  #print asd 
6490   
6491          # Plot statistics. 
6492          # Try plot some minimisation correlations. 
6493          if True: 
6494              selections = [None, ':2,3'] 
6495              for selection in selections: 
6496                  # Collect param values. 
6497                  analysis = 'min_ind' 
6498                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6499                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6500   
6501                  fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6502                  fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6503                  corr_data = [fig1, fig2] 
6504   
6505                  write_stats = True 
6506                  RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6507   
6508                  # Open stat file. 
6509                  if write_stats: 
6510                      for i, corr_data_i in enumerate(corr_data): 
6511                          data, methods, glob_inis = corr_data[i] 
6512                          data_x, data_y = data 
6513                          method_x, method_y = methods 
6514                          glob_ini_x, glob_ini_y = glob_inis 
6515   
6516                          file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6517   
6518                          if selection == None: 
6519                              file_name = file_name_ini + '_all.txt' 
6520                          else: 
6521                              file_name = file_name_ini + '_sel.txt' 
6522                          path = RDR.results_dir 
6523                          data = extract_data(file=file_name, dir=path) 
6524   
6525                          # Loop over the lines. 
6526                          for i, data_i in enumerate(data): 
6527                              print(i, data_i) 
6528   
6529          # Try plot some minimisation statistics. 
6530          if True: 
6531              # Collect param values. 
6532              #selections = [None, ':2,3'] 
6533              selections = [None, ':2,3'] 
6534              for selection in selections: 
6535                  analysis = 'min_ind' 
6536                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6537                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6538   
6539                  # Get param stats. 
6540                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6541   
6542                  ## Plot R2eff stats 
6543                  write_stats = True 
6544                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6545   
6546                  # Open stat file. 
6547                  if write_stats: 
6548                      if selection == None: 
6549                          file_name = '%s_stat_all.txt' % (analysis) 
6550                      else: 
6551                          file_name = '%s_stat_sel.txt' % (analysis) 
6552                      path = RDR.results_dir 
6553                      data = extract_data(file=file_name, dir=path) 
6554   
6555                      # Loop over the lines. 
6556                      for i, data_i in enumerate(data): 
6557                          print(i, data_i) 
6558   
6559   
6560          # Do minimisation clustered. 
6561          if True: 
6562              methods = ['FT', 'MDD'] 
6563              # Now calculate R2eff. 
6564              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6565   
6566              min_methods = [['FT'], ['MDD']] 
6567              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6568   
6569              #min_methods = [['FT']] 
6570              #min_list_glob_ini = [[128]] 
6571              selection = ':2,3' 
6572   
6573              for i, methods in enumerate(min_methods): 
6574                  list_glob_ini = min_list_glob_ini[i] 
6575   
6576                  if True: 
6577                      # First get data. 
6578                      if True: 
6579                          # First load all data. 
6580                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6581                       
6582                      # Then select spins. 
6583                      if True: 
6584                          # Deselect all spins. 
6585                          RDR.deselect_all(methods=methods, model='setup', model_from=MODEL_R2EFF, analysis='grid_setup', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6586                   
6587                          RDR.select_spin(spin_id=selection, methods=methods, model='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6588                   
6589                      # Then preset values. 
6590                      if True: 
6591                          # Set k_AB for Grid search. 
6592                          RDR.value_set(methods=methods, val=1000., param='kex', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6593                          RDR.value_set(methods=methods, val=0.95, param='pA', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6594                   
6595                      # Then set R20 
6596                      if True: 
6597                          # Set R20 from min R2eff in preparation for Grid search. 
6598                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6599                   
6600                      # Check and print parameters. 
6601                      if True: 
6602                          # Print for pipe name 
6603                          method = methods[0] 
6604                          glob_ini = list_glob_ini[0] 
6605   
6606                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup', glob_ini=glob_ini) 
6607                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6608                       
6609                      # Then Grid search. 
6610                      if True: 
6611                          # Do Grid search. 
6612                          RDR.minimise_grid_search(inc=200, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid', analysis_from='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6613                   
6614                      # Then cluster spins. 
6615                      if True: 
6616                          RDR.cluster_spins(spin_id=selection, methods=methods, model=MODEL_CR72, analysis='grid', list_glob_ini=list_glob_ini, force=True) 
6617               
6618                  # Then Minimise. 
6619                  if True: 
6620                      # Minimise 
6621                      RDR.opt_max_iterations = int(1e2) 
6622                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min', analysis_from='grid', list_glob_ini=list_glob_ini, force=False) 
6623   
6624          # Plot statistics. 
6625          # Try plot some minimisation correlations. 
6626          if True: 
6627              selection = ':2,3' 
6628              # Collect param values. 
6629              analysis = 'min' 
6630              min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6631              min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6632   
6633              fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6634              fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6635              corr_data = [fig1, fig2] 
6636   
6637              write_stats = True 
6638              RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6639   
6640              # Open stat file. 
6641              if write_stats: 
6642                  for i, corr_data_i in enumerate(corr_data): 
6643                      data, methods, glob_inis = corr_data[i] 
6644                      data_x, data_y = data 
6645                      method_x, method_y = methods 
6646                      glob_ini_x, glob_ini_y = glob_inis 
6647   
6648                      file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6649   
6650                      if selection == None: 
6651                          file_name = file_name_ini + '_all.txt' 
6652                      else: 
6653                          file_name = file_name_ini + '_sel.txt' 
6654                      path = RDR.results_dir 
6655                      data = extract_data(file=file_name, dir=path) 
6656   
6657                      # Loop over the lines. 
6658                      for i, data_i in enumerate(data): 
6659                          print(i, data_i) 
6660   
6661          # Try plot some minimisation statistics. 
6662          if True: 
6663              # Collect param values. 
6664              selections = [':2,3'] 
6665              for selection in selections: 
6666                  analysis = 'min' 
6667                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6668                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6669   
6670                  # Get param stats. 
6671                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6672   
6673                  ## Plot R2eff stats 
6674                  write_stats = True 
6675                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6676   
6677                  # Open stat file. 
6678                  if write_stats: 
6679                      if selection == None: 
6680                          file_name = '%s_stat_all.txt' % (analysis) 
6681                      else: 
6682                          file_name = '%s_stat_sel.txt' % (analysis) 
6683                      path = RDR.results_dir 
6684                      data = extract_data(file=file_name, dir=path) 
6685   
6686                      # Loop over the lines. 
6687                      for i, data_i in enumerate(data): 
6688                          print(i, data_i) 
6689   
6690   
6691   
6692 -    def test_r1rho_kjaergaard_auto(self): 
6693          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
6694   
6695          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6696   
6697          This uses the automatic analysis. 
6698   
6699          """ 
6700   
6701          # Cluster residues 
6702          cluster_ids = [ 
6703          ":13@N", 
6704          ":15@N", 
6705          ":16@N", 
6706          ":25@N", 
6707          ":26@N", 
6708          ":28@N", 
6709          ":39@N", 
6710          ":40@N", 
6711          ":41@N", 
6712          ":43@N", 
6713          ":44@N", 
6714          ":45@N", 
6715          ":49@N", 
6716          ":52@N", 
6717          ":53@N"] 
6718   
6719          # Load the data. 
6720          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
6721   
6722          # Test some of the sequence. 
6723          self.assertEqual(len(cdp.mol), 1) 
6724          self.assertEqual(cdp.mol[0].name, None) 
6725          self.assertEqual(len(cdp.mol[0].res), 48) 
6726   
6727          # Test the chemical shift data. 
6728          cs = [122.223, 122.162, 114.250, 125.852, 118.626, 117.449, 119.999, 122.610, 118.602, 118.291, 115.393, 
6729          121.288, 117.448, 116.378, 116.316, 117.263, 122.211, 118.748, 118.103, 119.421, 119.317, 119.386, 117.279, 
6730          122.103, 120.038, 116.698, 111.811, 118.639, 118.285, 121.318, 117.770, 119.948, 119.759, 118.314, 118.160, 
6731          121.442, 118.714, 113.080, 125.706, 119.183, 120.966, 122.361, 126.675, 117.069, 120.875, 109.372, 119.811, 126.048] 
6732   
6733          i = 0 
6734          for spin, spin_id in spin_loop(return_id=True): 
6735              # Check the chemical shift. 
6736              self.assertEqual(spin.chemical_shift, cs[i]) 
6737   
6738              # Increment the index. 
6739              i += 1 
6740   
6741          # Initialize counter 
6742          i = 0 
6743          j = 0 
6744          # Count instances of select/deselect 
6745          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
6746              if curspin.select == True: 
6747                  i += 1 
6748              if curspin.select == False: 
6749                  j += 1 
6750   
6751          # Test number of selected/deselected spins. 
6752          self.assertEqual(i, len(cluster_ids)) 
6753          self.assertEqual(j, 48-len(cluster_ids)) 
6754   
6755          # Check the initial setup. 
6756          self.assertEqual(cdp.mol[0].res[7].num, 13) 
6757          self.assertEqual(cdp.mol[0].res[7].spin[0].kex, ds.guess[':13@N'][6]) 
6758          self.assertEqual(cdp.mol[0].res[7].spin[0].ri_data['R1'], ds.ref[':13@N'][2]) 
6759   
6760          self.assertEqual(cdp.mol[0].res[9].num, 15) 
6761          self.assertEqual(cdp.mol[0].res[9].spin[0].kex, ds.guess[':15@N'][6]) 
6762          self.assertEqual(cdp.mol[0].res[9].spin[0].ri_data['R1'], ds.ref[':15@N'][2]) 
6763   
6764          self.assertEqual(cdp.mol[0].res[10].num, 16) 
6765          self.assertEqual(cdp.mol[0].res[10].spin[0].kex, ds.guess[':16@N'][6]) 
6766          self.assert_(hasattr(cdp.mol[0].res[10].spin[0], 'ri_data')) 
6767   
6768          self.assertEqual(cdp.mol[0].res[16].num, 25) 
6769          self.assertEqual(cdp.mol[0].res[16].spin[0].kex, ds.guess[':25@N'][6]) 
6770          self.assert_(hasattr(cdp.mol[0].res[16].spin[0], 'ri_data')) 
6771   
6772          self.assertEqual(cdp.mol[0].res[17].num, 26) 
6773          self.assertEqual(cdp.mol[0].res[17].spin[0].kex, ds.guess[':26@N'][6]) 
6774          self.assert_(hasattr(cdp.mol[0].res[17].spin[0], 'ri_data')) 
6775   
6776          self.assertEqual(cdp.mol[0].res[19].num, 28) 
6777          self.assertEqual(cdp.mol[0].res[19].spin[0].kex, ds.guess[':28@N'][6]) 
6778          self.assert_(hasattr(cdp.mol[0].res[19].spin[0], 'ri_data')) 
6779   
6780          self.assertEqual(cdp.mol[0].res[29].num, 39) 
6781          self.assertEqual(cdp.mol[0].res[29].spin[0].kex, ds.guess[':39@N'][6]) 
6782          self.assert_(hasattr(cdp.mol[0].res[29].spin[0], 'ri_data')) 
6783   
6784          self.assertEqual(cdp.mol[0].res[30].num, 40) 
6785          self.assertEqual(cdp.mol[0].res[30].spin[0].kex, ds.guess[':40@N'][6]) 
6786          self.assert_(hasattr(cdp.mol[0].res[30].spin[0], 'ri_data')) 
6787   
6788          self.assertEqual(cdp.mol[0].res[31].num, 41) 
6789          self.assertEqual(cdp.mol[0].res[31].spin[0].kex, ds.guess[':41@N'][6]) 
6790          self.assert_(hasattr(cdp.mol[0].res[31].spin[0], 'ri_data')) 
6791   
6792          self.assertEqual(cdp.mol[0].res[33].num, 43) 
6793          self.assertEqual(cdp.mol[0].res[33].spin[0].kex, ds.guess[':43@N'][6]) 
6794          self.assert_(hasattr(cdp.mol[0].res[33].spin[0], 'ri_data')) 
6795   
6796          self.assertEqual(cdp.mol[0].res[34].num, 44) 
6797          self.assertEqual(cdp.mol[0].res[34].spin[0].kex, ds.guess[':44@N'][6]) 
6798          self.assert_(hasattr(cdp.mol[0].res[34].spin[0], 'ri_data')) 
6799   
6800          self.assertEqual(cdp.mol[0].res[35].num, 45) 
6801          self.assertEqual(cdp.mol[0].res[35].spin[0].kex, ds.guess[':45@N'][6]) 
6802          self.assert_(hasattr(cdp.mol[0].res[35].spin[0], 'ri_data')) 
6803   
6804          self.assertEqual(cdp.mol[0].res[38].num, 49) 
6805          self.assertEqual(cdp.mol[0].res[38].spin[0].kex, ds.guess[':49@N'][6]) 
6806          self.assert_(hasattr(cdp.mol[0].res[38].spin[0], 'ri_data')) 
6807   
6808          self.assertEqual(cdp.mol[0].res[41].num, 52) 
6809          self.assertEqual(cdp.mol[0].res[41].spin[0].kex, ds.guess[':52@N'][6]) 
6810          self.assert_(hasattr(cdp.mol[0].res[41].spin[0], 'ri_data')) 
6811   
6812          self.assertEqual(cdp.mol[0].res[42].num, 53) 
6813          self.assertEqual(cdp.mol[0].res[42].spin[0].kex, ds.guess[':53@N'][6]) 
6814          self.assert_(hasattr(cdp.mol[0].res[42].spin[0], 'ri_data')) 
6815   
6816          # The dispersion models. 
6817          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
6818   
6819          # The grid search size (the number of increments per dimension). 
6820          GRID_INC = 4 
6821   
6822          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6823          MC_NUM = 3 
6824   
6825          # Model selection technique. 
6826          MODSEL = 'AIC' 
6827   
6828          # Execute the auto-analysis (fast). 
6829          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6830          OPT_FUNC_TOL = 1e-1 
6831          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6832          OPT_MAX_ITERATIONS = 1000 
6833          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6834   
6835          result_dir_name = ds.tmpdir 
6836   
6837          # Make all spins free 
6838          for curspin in cluster_ids: 
6839              self.interpreter.relax_disp.cluster('free spins', curspin) 
6840              # Shut them down 
6841              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
6842   
6843          # Select only a subset of spins for global fitting 
6844          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
6845          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
6846   
6847          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
6848          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
6849   
6850          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
6851          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
6852   
6853          # Run the analysis. 
6854          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
6855   
6856          # Check the kex value of residue 52 
6857          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
6858   
6859          # Print results for each model. 
6860          print("\n\n################") 
6861          print("Printing results") 
6862          print("################\n") 
6863          for model in MODELS: 
6864              # Skip R2eff model. 
6865              if model == MODEL_R2EFF: 
6866                  continue 
6867   
6868              # Switch to pipe. 
6869              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
6870              print("\nModel: %s" % (model)) 
6871   
6872              # Loop over the spins. 
6873              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
6874                  # Generate spin string. 
6875                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
6876   
6877                  # Loop over the parameters. 
6878                  print("Optimised parameters for spin: %s" % (spin_string)) 
6879                  for param in cur_spin.params + ['chi2']: 
6880                      # Get the value. 
6881                      if param in ['r1', 'r2']: 
6882                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
6883                              # Generate the R20 key. 
6884                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
6885   
6886                              # Get the value. 
6887                              value = getattr(cur_spin, param)[r20_key] 
6888   
6889                              # Print value. 
6890                              print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
6891   
6892                      # For all other parameters. 
6893                      else: 
6894                          # Get the value. 
6895                          value = getattr(cur_spin, param) 
6896   
6897                          # Print value. 
6898                          print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
6899   
6900          # Print the final pipe. 
6901          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % ('final')) 
6902          print("\nFinal pipe") 
6903   
6904   
6905 -    def test_r1rho_kjaergaard_auto_check_graphs(self): 
6906          """Check of plot_disp_curves() function, after optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'R2eff' model. 
6907   
6908          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6909   
6910          This uses the automatic analysis. 
6911   
6912          """ 
6913   
6914          # Cluster residues 
6915          cluster_ids = [ 
6916          ":52@N"] 
6917   
6918          # Load the data. 
6919          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
6920   
6921          # The dispersion models. 
6922          MODELS = [MODEL_R2EFF] 
6923   
6924          # The grid search size (the number of increments per dimension). 
6925          GRID_INC = 4 
6926   
6927          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6928          MC_NUM = 3 
6929   
6930          # Model selection technique. 
6931          MODSEL = 'AIC' 
6932   
6933          # Execute the auto-analysis (fast). 
6934          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6935          OPT_FUNC_TOL = 1e-1 
6936          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6937          OPT_MAX_ITERATIONS = 1000 
6938          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6939   
6940          result_dir_name = ds.tmpdir 
6941   
6942          # Make all spins free 
6943          for curspin in cluster_ids: 
6944              self.interpreter.relax_disp.cluster('free spins', curspin) 
6945              # Shut them down 
6946              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
6947   
6948          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
6949   
6950          # Run the analysis. 
6951          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
6952   
6953          # Check the graphs produced. 
6954          graph_comb = [ 
6955          [Y_AXIS_R2_EFF, X_AXIS_DISP, INTERPOLATE_DISP], 
6956          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_DISP], 
6957          [Y_AXIS_R2_R1RHO, X_AXIS_W_EFF, INTERPOLATE_DISP], 
6958          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_OFFSET] 
6959          ] 
6960   
6961          # Define expected folder names. 
6962          result_folders = MODELS 
6963   
6964          # Assign spin_id. 
6965          spin_id = ':52@N' 
6966   
6967          # Loop over result folders. 
6968          for result_folder in result_folders: 
6969              # Skip the model R2eff, which does not produce graphs. 
6970              if result_folder == MODEL_R2EFF: 
6971                  continue 
6972   
6973              # Loop over graphs. 
6974              for y_axis, x_axis, interpolate in graph_comb: 
6975                  # Determine file name: 
6976                  file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
6977   
6978                  # Make the file name. 
6979                  file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
6980   
6981                  # Get the file path. 
6982                  file_path = get_file_path(file_name, result_dir_name+sep+result_folder) 
6983   
6984                  print("Testing file access to graph: %s"%file_path) 
6985                  self.assert_(access(file_path, F_OK)) 
6986   
6987          # Start testing all possible combinations of graphs. 
6988          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
6989          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
6990          interpolate_types = [INTERPOLATE_DISP, INTERPOLATE_OFFSET] 
6991   
6992          result_dir_name = ds.tmpdir 
6993   
6994          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
6995          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep+'check_graphs' 
6996   
6997          for result_folder in result_folders: 
6998              # Skip the model R2eff, which does not produce graphs. 
6999              if result_folder == MODEL_R2EFF: 
7000                  continue 
7001   
7002              for y_axis in y_axis_types: 
7003                  for x_axis in x_axis_types: 
7004                      for interpolate in interpolate_types: 
7005                          # Determine file name: 
7006                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7007   
7008                          # Make the file name. 
7009                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7010   
7011                          # Write the curves. 
7012                          dir = result_dir_name+sep+result_folder 
7013                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
7014                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
7015   
7016                          # Get the file path. 
7017                          file_path = get_file_path(file_name, dir) 
7018   
7019                          # Test the plot file exists. 
7020                          print("Testing file access to graph: %s"%file_path) 
7021                          self.assert_(access(file_path, F_OK)) 
7022   
7023                          # Now open, and compare content, line by line. 
7024                          file_prod = open(file_path) 
7025                          lines_prod = file_prod.readlines() 
7026                          file_prod.close() 
7027   
7028                          # Define file to compare against. 
7029                          dir_comp = data_path+sep+result_folder 
7030                          file_path_comp = get_file_path(file_name, dir_comp) 
7031                          file_comp = open(file_path_comp) 
7032                          lines_comp = file_comp.readlines() 
7033                          file_comp.close() 
7034   
7035                          # Assert number of lines is equal. 
7036                          self.assertEqual(len(lines_prod), len(lines_comp)) 
7037                          for j in range(len(lines_prod)): 
7038                              # Make the string test 
7039                              first_char = lines_prod[j][0] 
7040                              if first_char in ["@", "&"]: 
7041                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
7042                              else: 
7043                                  # Split string in x, y, error. 
7044                                  # The error would change per run. 
7045                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
7046                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
7047                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
7048                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
7049   
7050   
7051 -    def test_r1rho_kjaergaard_missing_r1(self): 
7052          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
7053   
7054          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
7055   
7056          This uses the automatic analysis, with missing loading R1. 
7057   
7058          """ 
7059   
7060          # Cluster residues 
7061          cluster_ids = [ 
7062          ":13@N", 
7063          ":15@N", 
7064          ":16@N", 
7065          ":25@N", 
7066          ":26@N", 
7067          ":28@N", 
7068          ":39@N", 
7069          ":40@N", 
7070          ":41@N", 
7071          ":43@N", 
7072          ":44@N", 
7073          ":45@N", 
7074          ":49@N", 
7075          ":52@N", 
7076          ":53@N"] 
7077   
7078          # Load the data. 
7079          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
7080   
7081          # The dispersion models. 
7082          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
7083   
7084          # The grid search size (the number of increments per dimension). 
7085          GRID_INC = None 
7086   
7087          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7088          MC_NUM = 3 
7089   
7090          # Model selection technique. 
7091          MODSEL = 'AIC' 
7092   
7093          # Execute the auto-analysis (fast). 
7094          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7095          OPT_FUNC_TOL = 1e-25 
7096          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7097          OPT_MAX_ITERATIONS = 10000000 
7098          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7099   
7100          result_dir_name = ds.tmpdir 
7101   
7102          # Make all spins free 
7103          for curspin in cluster_ids: 
7104              self.interpreter.relax_disp.cluster('free spins', curspin) 
7105              # Shut them down 
7106              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7107   
7108          # Select only a subset of spins for global fitting 
7109          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
7110          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
7111   
7112          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
7113          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
7114   
7115          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7116          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
7117   
7118          # Point to directory with R2eff values, with 2000 MC simulations. 
7119          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000" 
7120   
7121          r1_fit = True 
7122   
7123          # Run the analysis. 
7124          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, pre_run_dir=prev_data_path, r1_fit=r1_fit) 
7125   
7126          # Verify the data. 
7127          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='MC2000') 
7128   
7129   
7130 -    def test_r2eff_read(self): 
7131          """Test the operation of the relax_disp.r2eff_read user function.""" 
7132   
7133          # The path to the data files. 
7134          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'800_MHz' 
7135   
7136          # Read the sequence data. 
7137          self.interpreter.sequence.read(file='66.667.in', dir=data_path, res_num_col=1) 
7138   
7139          # The ID. 
7140          id = 'test' 
7141   
7142          # Set up the metadata. 
7143          self.interpreter.spectrometer.frequency(id=id, frq=800e6) 
7144          self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7145   
7146          # Try reading the file. 
7147          self.interpreter.relax_disp.r2eff_read(id=id, file='66.667.in', dir=data_path, disp_frq=66.667, res_num_col=1, data_col=2, error_col=3) 
7148   
7149          # Check the global data. 
7150          data = [ 
7151              ['cpmg_frqs', {'test': 66.667}], 
7152              ['cpmg_frqs_list', [66.667]], 
7153              ['dispersion_points', 1], 
7154              ['exp_type', {'test': 'SQ CPMG'}], 
7155              ['exp_type_list', ['SQ CPMG']], 
7156              ['spectrometer_frq', {'test': 800000000.0}], 
7157              ['spectrometer_frq_count', 1], 
7158              ['spectrometer_frq_list', [800000000.0]], 
7159              ['spectrum_ids', ['test']] 
7160          ] 
7161          for name, value in data: 
7162              # Does it exist? 
7163              self.assert_(hasattr(cdp, name)) 
7164   
7165              # Check the object. 
7166              obj = getattr(cdp, name) 
7167              self.assertEqual(obj, value) 
7168   
7169          # Check the spin data. 
7170          data = [ 
7171              [1,       2.3035747e+04, 8.5467725e+01], 
7172              [2,       9.9629762e+04, 2.8322033e+02], 
7173              [3,       9.5663137e+04, 2.8632929e+02], 
7174              [4,       1.7089893e+05, 3.1089428e+02], 
7175              [5,       4.7323876e+04, 1.0084269e+02], 
7176              [6,       2.0199122e+04, 1.0135220e+02], 
7177              [7,       1.6655488e+05, 3.1609061e+02], 
7178              [8,       9.0061074e+04, 1.9176585e+02], 
7179              [10,      8.4726204e+04, 2.8898155e+02], 
7180              [11,      1.5050233e+05, 4.3138029e+02], 
7181              [12,      9.2998531e+04, 3.0440191e+02], 
7182              [13,      1.6343507e+05, 3.3144097e+02], 
7183              [14,      1.0137301e+05, 3.7314642e+02], 
7184              [15,      8.3407837e+04, 1.6546473e+02], 
7185              [16,      1.3819126e+05, 3.3388517e+02], 
7186              [17,      1.1010490e+05, 3.5639222e+02], 
7187              [18,      9.4324035e+04, 3.2343585e+02], 
7188              [19,      1.1135179e+05, 3.0706671e+02], 
7189              [20,      7.6339410e+04, 1.7377460e+02], 
7190              [21,      6.2008453e+04, 1.7327150e+02], 
7191              [22,      1.0590404e+05, 2.4814635e+02], 
7192              [23,      1.0630198e+05, 2.3601100e+02], 
7193              [24,      7.2996320e+04, 1.4952465e+02], 
7194              [25,      9.5486742e+04, 2.7080766e+02], 
7195              [26,      5.8067989e+04, 1.6820462e+02], 
7196              [27,     -1.7168510e+04, 2.2519560e+02], 
7197              [28,      1.6891473e+05, 2.3497525e+02], 
7198              [29,      9.4038555e+04, 2.0357593e+02], 
7199              [30,      2.1386951e+04, 2.2153532e+02], 
7200              [31,      9.3982899e+04, 2.0937056e+02], 
7201              [32,      8.6097484e+04, 2.3868467e+02], 
7202              [33,      1.0194337e+05, 2.7370704e+02], 
7203              [34,      8.5683111e+04, 2.0838076e+02], 
7204              [35,      8.6985768e+04, 2.0889310e+02], 
7205              [36,      8.6011237e+04, 1.7498390e+02], 
7206              [37,      1.0984097e+05, 2.7622998e+02], 
7207              [38,      8.7017879e+04, 2.6547994e+02], 
7208              [39,      9.1682649e+04, 5.2777676e+02], 
7209              [40,      7.6370440e+04, 1.9873214e+02], 
7210              [41,      9.1393531e+04, 2.4483824e+02], 
7211              [42,      1.1017111e+05, 2.8020699e+02], 
7212              [43,      9.4552366e+04, 3.4394150e+02], 
7213              [44,      1.2858281e+05, 6.8449252e+02], 
7214              [45,      7.4583525e+04, 1.9544210e+02], 
7215              [46,      9.2087490e+04, 2.0491066e+02], 
7216              [47,      9.7507255e+04, 2.5162839e+02], 
7217              [48,      1.0033842e+05, 2.7566430e+02], 
7218              [49,      1.3048305e+05, 2.6797466e+02], 
7219              [50,      1.0546796e+05, 1.9304384e+02], 
7220              [51,      9.3099697e+04, 2.0773311e+02], 
7221              [52,      4.6863758e+04, 1.3169068e+02], 
7222              [53,      6.1055806e+04, 1.5448477e+02], 
7223              [55,      6.8629994e+04, 1.6868673e+02], 
7224              [56,      1.1005552e+05, 2.1940465e+02], 
7225              [57,      1.0572760e+05, 1.9768486e+02], 
7226              [58,      1.1176950e+05, 3.0009610e+02], 
7227              [59,      9.8758603e+04, 3.3803895e+02], 
7228              [60,      9.9517201e+04, 3.5137994e+02], 
7229              [61,      5.4357946e+04, 2.5896579e+02], 
7230              [62,      1.0899978e+05, 2.8720371e+02], 
7231              [63,      8.4549759e+04, 4.1401837e+02], 
7232              [64,      5.5014550e+04, 2.1135781e+02], 
7233              [65,      8.0569666e+04, 2.3249709e+02], 
7234              [66,      1.2936610e+05, 3.5218725e+02], 
7235              [67,      3.6438010e+04, 8.7924003e+01], 
7236              [70,      3.8763157e+04, 1.3325040e+02], 
7237              [71,      8.5711411e+04, 2.9316183e+02], 
7238              [72,      3.3211541e+04, 1.2182123e+02], 
7239              [73,      3.2070576e+04, 1.2305430e+02] 
7240          ] 
7241          for res_num, value, error in data: 
7242              # Get the spin. 
7243              spin = return_spin(spin_id=":%s"%res_num) 
7244   
7245              # Check the values. 
7246              self.assertEqual(spin.r2eff['sq_cpmg_800.00000000_0.000_66.667'], value) 
7247              self.assertEqual(spin.r2eff_err['sq_cpmg_800.00000000_0.000_66.667'], error) 
7248   
7249   
7250 -    def test_r2eff_read_spin(self): 
7251          """Test the operation of the relax_disp.r2eff_read_spin user function.""" 
7252   
7253          # The path to the data files. 
7254          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
7255   
7256          # Generate the sequence. 
7257          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
7258          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
7259          self.interpreter.spin.isotope('1H', spin_id='@H') 
7260          self.interpreter.spin.isotope('15N', spin_id='@N') 
7261   
7262          # Build the experiment IDs. 
7263          H_disp_points = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
7264          N_disp_points = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
7265          ids = [] 
7266          for value in H_disp_points: 
7267              ids.append('1H_CPMG_%s' % value) 
7268          for value in N_disp_points: 
7269              ids.append('15N_CPMG_%s' % value) 
7270          print("\n\nThe experiment IDs are %s." % ids) 
7271   
7272          # Set up the metadata for the experiments. 
7273          for id in ids: 
7274              self.interpreter.spectrometer.frequency(id=id, frq=500e6) 
7275              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7276          for value in H_disp_points: 
7277              self.interpreter.relax_disp.cpmg_setup(spectrum_id='1H_CPMG_%s' % value, cpmg_frq=value) 
7278          for value in N_disp_points: 
7279              self.interpreter.relax_disp.cpmg_setup(spectrum_id='15N_CPMG_%s' % value, cpmg_frq=value) 
7280   
7281          # Loop over the experiments. 
7282          for id, file, spin_id in [['1H_CPMG', 'hs_500.res', ':9@H'], ['15N_CPMG', 'ns_500.res', ':9@N']]: 
7283              # Try reading the file. 
7284              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
7285   
7286          # Check the global data. 
7287          data = [ 
7288              ['cpmg_frqs', {'1H_CPMG_667.0': 667.0, '1H_CPMG_1067.0': 1067.0, '15N_CPMG_350.0': 350.0, '1H_CPMG_933.0': 933.0, '15N_CPMG_50.0': 50.0, '15N_CPMG_100.0': 100.0, '1H_CPMG_400.0': 400.0, '1H_CPMG_533.0': 533.0, '1H_CPMG_800.0': 800.0, '15N_CPMG_900.0': 900.0, '15N_CPMG_150.0': 150.0, '15N_CPMG_800.0': 800.0, '1H_CPMG_267.0': 267.0, '1H_CPMG_2667.0': 2667.0, '15N_CPMG_300.0': 300.0, '1H_CPMG_133.0': 133.0, '15N_CPMG_700.0': 700.0, '1H_CPMG_67.0': 67.0, '15N_CPMG_400.0': 400.0, '15N_CPMG_250.0': 250.0, '1H_CPMG_2133.0': 2133.0, '1H_CPMG_1600.0': 1600.0, '15N_CPMG_200.0': 200.0, '15N_CPMG_1000.0': 1000.0, '15N_CPMG_500.0': 500.0, '15N_CPMG_600.0': 600.0}], 
7289              ['cpmg_frqs_list', [50.0, 67.0, 100.0, 133.0, 150.0, 200.0, 250.0, 267.0, 300.0, 350.0, 400.0, 500.0, 533.0, 600.0, 667.0, 700.0, 800.0, 900.0, 933.0, 1000.0, 1067.0, 1600.0, 2133.0, 2667.0]], 
7290              ['dispersion_points', 24], 
7291              ['exp_type', {'1H_CPMG_667.0': 'SQ CPMG', '1H_CPMG_1067.0': 'SQ CPMG', '15N_CPMG_350.0': 'SQ CPMG', '1H_CPMG_933.0': 'SQ CPMG', '15N_CPMG_50.0': 'SQ CPMG', '15N_CPMG_100.0': 'SQ CPMG', '1H_CPMG_400.0': 'SQ CPMG', '1H_CPMG_533.0': 'SQ CPMG', '1H_CPMG_800.0': 'SQ CPMG', '15N_CPMG_900.0': 'SQ CPMG', '15N_CPMG_150.0': 'SQ CPMG', '15N_CPMG_800.0': 'SQ CPMG', '1H_CPMG_267.0': 'SQ CPMG', '1H_CPMG_2667.0': 'SQ CPMG', '15N_CPMG_300.0': 'SQ CPMG', '1H_CPMG_133.0': 'SQ CPMG', '15N_CPMG_700.0': 'SQ CPMG', '1H_CPMG_67.0': 'SQ CPMG', '15N_CPMG_400.0': 'SQ CPMG', '15N_CPMG_250.0': 'SQ CPMG', '1H_CPMG_2133.0': 'SQ CPMG', '1H_CPMG_1600.0': 'SQ CPMG', '15N_CPMG_200.0': 'SQ CPMG', '15N_CPMG_1000.0': 'SQ CPMG', '15N_CPMG_500.0': 'SQ CPMG', '15N_CPMG_600.0': 'SQ CPMG'}], 
7292              ['exp_type_list', ['SQ CPMG']], 
7293              ['spectrometer_frq', {'1H_CPMG_667.0': 500000000.0, '1H_CPMG_1067.0': 500000000.0, '15N_CPMG_350.0': 500000000.0, '1H_CPMG_933.0': 500000000.0, '15N_CPMG_50.0': 500000000.0, '15N_CPMG_100.0': 500000000.0, '1H_CPMG_400.0': 500000000.0, '1H_CPMG_533.0': 500000000.0, '1H_CPMG_800.0': 500000000.0, '15N_CPMG_900.0': 500000000.0, '15N_CPMG_150.0': 500000000.0, '15N_CPMG_800.0': 500000000.0, '1H_CPMG_267.0': 500000000.0, '1H_CPMG_2667.0': 500000000.0, '15N_CPMG_300.0': 500000000.0, '1H_CPMG_133.0': 500000000.0, '15N_CPMG_700.0': 500000000.0, '1H_CPMG_67.0': 500000000.0, '15N_CPMG_400.0': 500000000.0, '15N_CPMG_250.0': 500000000.0, '1H_CPMG_2133.0': 500000000.0, '1H_CPMG_1600.0': 500000000.0, '15N_CPMG_200.0': 500000000.0, '15N_CPMG_1000.0': 500000000.0, '15N_CPMG_500.0': 500000000.0, '15N_CPMG_600.0': 500000000.0}], 
7294              ['spectrometer_frq_count', 1], 
7295              ['spectrometer_frq_list', [500000000.0]], 
7296              ['spectrum_ids', ['1H_CPMG_67.0', '1H_CPMG_133.0', '1H_CPMG_267.0', '1H_CPMG_400.0', '1H_CPMG_533.0', '1H_CPMG_667.0', '1H_CPMG_800.0', '1H_CPMG_933.0', '1H_CPMG_1067.0', '1H_CPMG_1600.0', '1H_CPMG_2133.0', '1H_CPMG_2667.0', '15N_CPMG_50.0', '15N_CPMG_100.0', '15N_CPMG_150.0', '15N_CPMG_200.0', '15N_CPMG_250.0', '15N_CPMG_300.0', '15N_CPMG_350.0', '15N_CPMG_400.0', '15N_CPMG_500.0', '15N_CPMG_600.0', '15N_CPMG_700.0', '15N_CPMG_800.0', '15N_CPMG_900.0', '15N_CPMG_1000.0']] 
7297          ] 
7298          for name, value in data: 
7299              # Does it exist? 
7300              self.assert_(hasattr(cdp, name)) 
7301   
7302              # Check the object. 
7303              obj = getattr(cdp, name) 
7304              if not isinstance(data, dict): 
7305                  self.assertEqual(obj, value) 
7306   
7307              # Check the global dictionary data. 
7308              else: 
7309                  for id in ids: 
7310                      self.assertEqual(obj[id], value[id]) 
7311   
7312          # Check the spin data. 
7313          h_data = [ 
7314              [  67.0,  21.47924,   0.42958], 
7315              [ 133.0,  16.73898,   0.33478], 
7316              [ 267.0,   9.97357,   0.19947], 
7317              [ 400.0,   8.23877,   0.24737], 
7318              [ 533.0,   7.59290,   0.24263], 
7319              [ 667.0,   7.45843,   0.24165], 
7320              [ 800.0,   7.11222,   0.23915], 
7321              [ 933.0,   7.40880,   0.24129], 
7322              [1067.0,   6.55191,   0.16629], 
7323              [1600.0,   6.72177,   0.23637], 
7324              [2133.0,   7.09629,   0.23904], 
7325              [2667.0,   7.14675,   0.23940] 
7326          ] 
7327          for disp_point, value, error in h_data: 
7328              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7329              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
7330              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
7331          n_data = [ 
7332              [  50.0,  27.15767,   0.54315], 
7333              [ 100.0,  26.55781,   0.53116], 
7334              [ 150.0,  24.73462,   0.49469], 
7335              [ 200.0,  20.98617,   0.41972], 
7336              [ 250.0,  17.82442,   0.35649], 
7337              [ 300.0,  15.55352,   0.31107], 
7338              [ 350.0,  13.78958,   0.27579], 
7339              [ 400.0,  12.48334,   0.24967], 
7340              [ 500.0,  11.55724,   0.23114], 
7341              [ 600.0,  10.53874,   0.21077], 
7342              [ 700.0,  10.07395,   0.20148], 
7343              [ 800.0,   9.62952,   0.19259], 
7344              [ 900.0,   9.49994,   0.19000], 
7345              [1000.0,   8.71350,   0.17427] 
7346          ] 
7347          for disp_point, value, error in n_data: 
7348              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7349              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff[id], value) 
7350              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff_err[id], error) 
7351   
7352   
7353 -    def test_r2eff_fit_fixed_time(self): 
7354          """Test the relaxation dispersion 'R2eff' model for fixed time data in the auto-analysis.""" 
7355   
7356          # Execute the script. 
7357          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r2eff_calc.py') 
7358   
7359   
7360 -    def test_read_r2eff(self): 
7361          """Test the reading of a file containing r2eff values.""" 
7362   
7363          # Create the sequence data, and name the spins. 
7364          self.interpreter.residue.create(1, 'Gly') 
7365          self.interpreter.residue.create(2, 'Gly') 
7366          self.interpreter.residue.create(3, 'Gly') 
7367   
7368          # Read the file. 
7369          self.interpreter.relax_data.read(ri_id='R2eff.600', ri_type='R2eff', frq=600*1e6, file='r2eff.out', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r2eff', res_num_col=1, res_name_col=2, data_col=3, error_col=4) 
7370   
7371          # Test the data. 
7372          self.assertEqual(cdp.mol[0].res[0].spin[0].ri_data['R2eff.600'], 15.000) 
7373          self.assertEqual(cdp.mol[0].res[1].spin[0].ri_data['R2eff.600'], 4.2003) 
7374          self.assertEqual(cdp.mol[0].res[2].spin[0].ri_data['R2eff.600'], 7.2385) 
7375   
7376   
7377 -    def test_r20_from_min_r2eff_cpmg(self): 
7378          """Test speeding up grid search. Support requst sr #3151 U{https://gna.org/support/index.php?3151}. 
7379   
7380          User function to set the R20 parameters in the default grid search using the minimum R2eff value. 
7381   
7382          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7383          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7384   
7385          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7386          Data is for experiment at 25 degree Celcius. 
7387          """ 
7388   
7389          # Base data setup. 
7390          pipe_name = 'base pipe' 
7391          pipe_type = 'relax_disp' 
7392          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7393          select_spin_index = list(range(0, 1)) 
7394          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7395   
7396          # Generate r20 key. 
7397          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7398          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7399   
7400          ## Now prepare for MODEL calculation. 
7401          MODEL = "CR72" 
7402   
7403          # Change pipe. 
7404          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7405          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7406          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7407   
7408          # Then select model. 
7409          self.interpreter.relax_disp.select_model(model=MODEL) 
7410   
7411          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7412          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7413   
7414          # Test result, for normal run. 
7415          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7416              # Get the spin_params. 
7417              spin_params = spin.params 
7418   
7419              # Defined fixed values for testing. 
7420              if spin_id == ":10@N": 
7421                  self.assertEqual(spin.r2[r20_key_600], 20.282732526087106) 
7422                  self.assertEqual(spin.r2[r20_key_500], 18.475299724356649) 
7423   
7424              # Print out. 
7425              print("r2_600=%2.2f r2_500=%2.2f spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin_id, resi, resn)) 
7426   
7427              # Testing the r2 values for the different fields are not the same. 
7428              self.assert_(spin.r2[r20_key_600] != spin.r2[r20_key_500]) 
7429   
7430              # Test values are larger than 0. 
7431              self.assert_(spin.r2[r20_key_600] > 0.0) 
7432              self.assert_(spin.r2[r20_key_500] > 0.0) 
7433   
7434              # Loop over the experiment settings. 
7435              r2eff_600 = [] 
7436              r2eff_500 = [] 
7437              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
7438                  # Create the data key. 
7439                  data_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
7440   
7441                  # Extract the r2 eff data. 
7442                  r2eff = spin.r2eff[data_key] 
7443                  if frq == 599.8908617*1E6: 
7444                      r2eff_600.append(r2eff) 
7445                  elif frq == 499.862139*1E6: 
7446                      r2eff_500.append(r2eff) 
7447   
7448              # Sort values. 
7449              r2eff_600.sort() 
7450              r2eff_500.sort() 
7451   
7452              # Test values again. 
7453              print("For r20 600MHz min r2eff=%3.3f."%(min(r2eff_600))) 
7454              print(r2eff_600) 
7455              self.assertEqual(spin.r2[r20_key_600], min(r2eff_600)) 
7456              print("") 
7457   
7458              print("For r20 500MHz min r2eff=%3.3f."%(min(r2eff_500))) 
7459              print(r2eff_500) 
7460              self.assertEqual(spin.r2[r20_key_500], min(r2eff_500)) 
7461              print("") 
7462   
7463          print("###########################################") 
7464          print("Trying GRID SEARCH for minimum R2eff values") 
7465   
7466          ### Test just the Grid search. 
7467          GRID_INC = 5 
7468   
7469          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7470   
7471          ### Then test the value.set function. 
7472          # Change pipe. 
7473          pipe_name_MODEL = "%s_%s_2"%(pipe_name, MODEL) 
7474          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7475          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7476   
7477          # Then select model. 
7478          self.interpreter.relax_disp.select_model(model=MODEL) 
7479   
7480          # Then set the standard parameter values. 
7481          for param in spin_params: 
7482              print("Setting standard parameter for param: %s"%param) 
7483              self.interpreter.value.set(param=param, index=None) 
7484   
7485          # Test result, for normal run. 
7486          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7487              # Print out. 
7488              print("r2_600=%2.2f r2_500=%2.2f pA=%2.2f, dw=%2.2f, kex=%2.2f, spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin.pA, spin.dw, spin.kex, spin_id, resi, resn)) 
7489   
7490              # Testing the r2 values. 
7491              self.assertEqual(spin.r2[r20_key_600], 10.00) 
7492              self.assertEqual(spin.r2[r20_key_500], 10.00) 
7493              self.assertEqual(spin.pA, 0.9) 
7494              self.assertEqual(spin.dw, 1.0) 
7495              self.assertEqual(spin.kex, 1000.0) 
7496   
7497          print("###########################################") 
7498          print("Trying GRID SEARCH for standard R2eff values") 
7499   
7500          ### Test just the Grid search. 
7501          GRID_INC = 5 
7502   
7503          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7504   
7505          ### Run auto_analysis. 
7506          # The grid search size (the number of increments per dimension). 
7507          GRID_INC = 5 
7508   
7509          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7510          MC_NUM = 3 
7511   
7512          # Model selection technique. 
7513          MODSEL = 'AIC' 
7514   
7515          # Execute the auto-analysis (fast). 
7516          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7517          OPT_FUNC_TOL = 1e-1 
7518          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7519          OPT_MAX_ITERATIONS = 1000 
7520          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7521   
7522          # Run the analysis. 
7523          relax_disp.Relax_disp(pipe_name=pipe_name_r2eff, results_dir=ds.tmpdir, models=[MODEL], grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, set_grid_r20=True) 
7524   
7525   
7526 -    def test_show_apod_extract(self): 
7527          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7528   
7529          # The path to the data files. 
7530          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7531   
7532          # Define file name. 
7533          file_name = '128_0_FT.ft2' 
7534   
7535          # Call function. 
7536          get_output = show_apod_extract(file_name=file_name, dir=data_path) 
7537   
7538          # Define how output should look like. 
7539          # The output from showApod differs slightly according to NMRPipe version. But 'Noise Std Dev' is the same. 
7540          # Dont test lines which can differ. 
7541          show_apod_ver = [ 
7542              'REMARK Effect of Processing on Peak Parameters and Noise for %s'%(data_path+sep+file_name), 
7543              'REMARK Automated Noise Std Dev in Processed Data: 8583.41', 
7544              'REMARK Noise Std Dev Before Processing H1 and N15: 60.6558', 
7545              '', 
7546              'VARS   AXIS LABEL  TSIZE FSIZE LW_ADJ LW_FINAL HI_FACTOR VOL_FACTOR SIGMA_FACTOR', 
7547              'FORMAT %s   %-8s   %4d   %4d   %7.4f  %7.4f    %.4e      %.4e       %.4e'] 
7548              #'', 
7549              #'       X    H1       800  2048 0.8107 3.7310   4.9903e-03 9.8043e-04 5.2684e-02', 
7550              #'       Y    N15      128   256 0.7303 3.0331   3.1260e-02 7.8434e-03 1.3413e-01'] 
7551   
7552          for i, line in enumerate(show_apod_ver): 
7553              line_ver = get_output[i] 
7554   
7555              print(line) 
7556              if line[:50] == 'REMARK Noise Std Dev Before Processing H1 and N15:': 
7557                  continue 
7558              # Make the string test 
7559              self.assertEqual(line, line_ver) 
7560   
7561   
7562 -    def test_show_apod_rmsd(self): 
7563          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7564   
7565          # The path to the data files. 
7566          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7567   
7568          # Define file name. 
7569          file_name = '128_0_FT.ft2' 
7570   
7571          # Call function. 
7572          rmsd = show_apod_rmsd(file_name=file_name, dir=data_path) 
7573   
7574          # Assert. 
7575          self.assertEqual(rmsd, 8583.41) 
7576   
7577   
7578 -    def test_show_apod_rmsd_dir_to_files(self): 
7579          """Test searching for all NMRPipe spectrum files in dir, call showApod, and write to files.""" 
7580   
7581          # The path to the data files. 
7582          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7583   
7584          # Call function, and get all file names. 
7585          wfile_paths = show_apod_rmsd_dir_to_files(file_ext='.ft2', dir=data_path, outdir=self.tmpdir) 
7586   
7587          # Loop over file_paths. 
7588          for wfile_path in wfile_paths: 
7589              # Open the file. 
7590              get_data = extract_data(file=wfile_path) 
7591   
7592              # Extract line 0, column 0. 
7593              test = float(get_data[0][0]) 
7594   
7595              # Assert. 
7596              self.assertEqual(test, 8583.41) 
7597   
7598   
7599 -    def test_show_apod_rmsd_to_file(self): 
7600          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod, and write to file.""" 
7601   
7602          # The path to the data files. 
7603          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7604   
7605          # Define file name. 
7606          file_name = '128_0_FT.ft2' 
7607   
7608          # Call function, and get file name. 
7609          wfile_path = show_apod_rmsd_to_file(file_name=file_name, dir=data_path, outdir=self.tmpdir) 
7610   
7611          # Open the file. 
7612          get_data = extract_data(file=wfile_path) 
7613   
7614          # Extract line 0, column 0. 
7615          test = float(get_data[0][0]) 
7616   
7617          # Assert. 
7618          self.assertEqual(test, 8583.41) 
7619   
7620   
7621 -    def test_sod1wt_t25_bug_21954_order_error_analysis(self): 
7622          """Error analysis of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7623   
7624          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7625          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7626   
7627          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7628          Data is for experiment at 25 degree Celcius. 
7629   
7630          bug #21954 U{https://gna.org/bugs/index.php?21954}: Order of spectrum.error_analysis is important. 
7631          """ 
7632   
7633          # Base data setup. 
7634          pipe_name = 'base pipe' 
7635          pipe_type = 'relax_disp' 
7636          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7637          select_spin_index = list(range(0, 1)) 
7638          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7639   
7640          # Define replicated 
7641          repl_A = ['Z_A1', 'Z_A15'] 
7642          repl_B = ['Z_B1', 'Z_B18'] 
7643   
7644          # Loop over spectrum ID, and sort them 
7645          spectrum_ids_A = [] 
7646          spectrum_ids_B = [] 
7647          for spectrum_id in cdp.spectrum_ids: 
7648              if "A" in spectrum_id: 
7649                  spectrum_ids_A.append(spectrum_id) 
7650              elif "B" in spectrum_id: 
7651                  spectrum_ids_B.append(spectrum_id) 
7652   
7653          # To clean up old error analysis, delete attributes 
7654          delattr(cdp, "var_I") 
7655          delattr(cdp, "sigma_I") 
7656   
7657          # Perform error analysis 
7658          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7659          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7660   
7661          # Loop over spins, save errors to list 
7662          Errors_A_B = [] 
7663          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7664              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7665              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7666              Errors_A_B.append([A_err, B_err]) 
7667   
7668          # To clean up old error analysis, delete attributes 
7669          delattr(cdp, "var_I") 
7670          delattr(cdp, "sigma_I") 
7671   
7672          # Perform error analysis. Order is important 
7673          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7674          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7675   
7676          # Loop over spins, save errors to list 
7677          Errors_B_A = [] 
7678          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7679              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7680              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7681              Errors_B_A.append([A_err, B_err]) 
7682   
7683          # Make test for order of error 
7684          for i in range(len(Errors_A_B)): 
7685              Error_A_B = Errors_A_B[i] 
7686              Error_B_A = Errors_B_A[i] 
7687              self.assertAlmostEqual(Error_A_B[0], Error_B_A[0], 4) 
7688              self.assertAlmostEqual(Error_A_B[1], Error_B_A[1], 4) 
7689   
7690          # Make further tests for fixed values 
7691          std_A = math.sqrt((cdp.var_I[repl_A[0]] + cdp.var_I[repl_A[1]])/2) 
7692          std_A_fix = 2785.7263335738567 
7693   
7694          for id_A in spectrum_ids_A: 
7695              self.assertEqual(cdp.sigma_I[id_A], std_A) 
7696              self.assertAlmostEqual(cdp.sigma_I[id_A], std_A_fix, 7) 
7697   
7698          std_B = math.sqrt((cdp.var_I[repl_B[0]] + cdp.var_I[repl_B[1]])/2) 
7699          std_B_fix = 4967.3772030667988 
7700   
7701          for id_B in spectrum_ids_B: 
7702              self.assertEqual(cdp.sigma_I[id_B], std_B) 
7703              self.assertAlmostEqual(cdp.sigma_I[id_B], std_B_fix, 7) 
7704   
7705   
7706 -    def test_sod1wt_t25_to_cr72(self): 
7707          """Optimisation of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7708   
7709          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7710          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7711   
7712          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7713          Data is for experiment at 25 degree Celcius. 
7714          """ 
7715   
7716          # Base data setup. 
7717          pipe_name = 'base pipe' 
7718          pipe_type = 'relax_disp' 
7719          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7720          select_spin_index = list(range(0, 2)) 
7721          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7722   
7723          # Generate r20 key. 
7724          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7725          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7726   
7727          ## Now prepare for MODEL calculation. 
7728          MODEL = "CR72" 
7729   
7730          # Change pipe. 
7731          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7732          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7733          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7734   
7735          # Then select model. 
7736          self.interpreter.relax_disp.select_model(model=MODEL) 
7737   
7738          # GRID inc of 7 was found to be appropriate not to find pA = 0.5. 
7739          GRID_INC = 7 
7740   
7741          # Store grid and minimisations results. 
7742          grid_results = [] 
7743          mini_results = [] 
7744          clust_results = [] 
7745   
7746          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7747          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7748   
7749          # Deselect insignificant spins. 
7750          self.interpreter.relax_disp.insignificance(level=1.0) 
7751   
7752          # Perform Grid Search. 
7753          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7754   
7755          # Store result. 
7756          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7757              # Store grid results. 
7758              grid_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7759   
7760          ## Now do minimisation. 
7761          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7762          set_func_tol = 1e-9 
7763          set_max_iter = 100000 
7764          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7765   
7766          # Store result. 
7767          pA_values = [] 
7768          kex_values = [] 
7769          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7770              # Store minimisation results. 
7771              mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7772   
7773              # Store pA values. 
7774              pA_values.append(spin.pA) 
7775   
7776              # Store kex values. 
7777              kex_values.append(spin.kex) 
7778   
7779          print("\n# Now print before and after minimisation.\n") 
7780   
7781          # Print results. 
7782          for i in range(len(grid_results)): 
7783              # Get values. 
7784              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7785              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7786   
7787              print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7788              print("MIN  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7789   
7790          ## Prepare for clustering 
7791          # Change pipe. 
7792          pipe_name_MODEL_CLUSTER = "%s_%s_Cluster"%(pipe_name, MODEL) 
7793          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL_CLUSTER) 
7794          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL_CLUSTER) 
7795   
7796          # Then select model. 
7797          self.interpreter.relax_disp.select_model(model=MODEL) 
7798   
7799          # Define cluster id. 
7800          cluster_id = 'clust' 
7801   
7802          # Loop over spins to cluster them. 
7803          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7804              self.interpreter.relax_disp.cluster(cluster_id, spin_id) 
7805   
7806          # Copy over values. 
7807          self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL, pipe_to=pipe_name_MODEL_CLUSTER) 
7808   
7809          # Test the median values is correct 
7810          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7811              print(pA_values) 
7812              # The the median pA value returned. 
7813              self.assertEqual(median(pA_values), spin.pA) 
7814   
7815              # The the median kex value returned. 
7816              self.assertEqual(median(kex_values), spin.kex) 
7817   
7818          ## Now do minimisation. 
7819          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7820   
7821          # Store result. 
7822          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7823              # Store clust results. 
7824              clust_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7825   
7826              # Store the outcome of the clustering minimisation. 
7827              clust_pA = spin.pA 
7828              clust_kex = spin.kex 
7829   
7830          print("\n# Now testing.\n") 
7831   
7832          # Define results 
7833          test_res = {} 
7834          test_res[':10@N'] = {} 
7835          test_res[':10@N']['r2600'] = 18.429755324773360 
7836          test_res[':10@N']['r2500'] = 16.981349161968630 
7837          test_res[':10@N']['dw'] = 2.700755859433969 
7838          test_res[':10@N']['pA'] = 0.971531659288657 
7839          test_res[':10@N']['kex'] = 3831.766337047963134 
7840          test_res[':11@N'] = {} 
7841          test_res[':11@N']['r2600'] = 18.193409421115213 
7842          test_res[':11@N']['r2500'] = 17.308838135567765 
7843          test_res[':11@N']['dw'] = 2.706650302761793 
7844          test_res[':11@N']['pA'] = 0.971531659288657 
7845          test_res[':11@N']['kex'] = 3831.766337047963134 
7846   
7847          # Then make tests. 
7848          for i in range(len(grid_results)): 
7849              # Get values. 
7850              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7851              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7852              c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn = clust_results[i] 
7853   
7854              print("%s GRID   r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7855              print("%s MIN    r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7856              print("%s Clust  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn)) 
7857   
7858              # Make tests. 
7859              self.assertEqual(clust_pA, c_pA) 
7860              self.assertEqual(clust_kex, c_kex) 
7861   
7862              # Test values. 
7863              if c_spin_id in test_res: 
7864                  self.assertAlmostEqual(c_r2_600, test_res[c_spin_id]['r2600'], 4) 
7865                  self.assertAlmostEqual(c_r2_500, test_res[c_spin_id]['r2500'], 4) 
7866                  self.assertAlmostEqual(c_dw, test_res[c_spin_id]['dw'], 3) 
7867                  self.assertAlmostEqual(c_pA, test_res[c_spin_id]['pA'], 5) 
7868                  self.assertAlmostEqual(c_kex, test_res[c_spin_id]['kex'], 1) 
7869   
7870          # Save disp graph to temp. 
7871          #self.interpreter.relax_disp.plot_disp_curves(dir="~"+sep+"test", num_points=1000, extend=500.0, force=True). 
7872   
7873   
7874 -    def test_sod1wt_t25_to_sherekhan_input(self): 
7875          """Conversion of SOD1-WT CPMG R2eff values into input files for sherekhan. 
7876   
7877          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7878          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7879   
7880          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7881          Data is for experiment at 25 degree Celcius. 
7882          """ 
7883   
7884          # Base data setup. 
7885          pipe_name = 'base pipe' 
7886          pipe_type = 'relax_disp' 
7887          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7888          select_spin_index = list(range(0, 2)) 
7889          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7890   
7891          # Generate r20 key. 
7892          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7893          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7894   
7895          # Cluster everything, to analyse together. 
7896          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-1000") 
7897   
7898          # Write input 
7899          self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=ds.tmpdir) 
7900   
7901          # Check the r2eff set files. 
7902          print("\nChecking the R2eff input set files.") 
7903          files = [[ds.tmpdir + sep + 'cluster1', 'sherekhan_frq1.in'], [ ds.tmpdir + sep + 'cluster1', 'sherekhan_frq2.in']] 
7904   
7905          # First check file exists 
7906          for dir, file in files: 
7907              print(dir+sep+file) 
7908              self.assert_(access(dir+sep+file, F_OK)) 
7909   
7910          # Define how files should look like 
7911          data_set_600 = [ 
7912               "60.8272464287\n", 
7913               "0.06\n", 
7914               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
7915               "# G10\n", 
7916               "              33.333       26.53556078711      0.5236104771163\n", 
7917               "              66.667       25.29735243318        0.48766574122\n", 
7918               "                 100       25.09470361403      0.4820438864671\n", 
7919               "             133.333       25.15603274331      0.4837377286085\n", 
7920               "             166.667       24.27213341753      0.4599457904395\n", 
7921               "                 200       24.00364120328      0.4529773198905\n", 
7922               "             266.667       24.03511395168      0.4537880662536\n", 
7923               "                 300       23.04761040024      0.4291039120557\n", 
7924               "             333.333       22.95530300787      0.4268745963972\n", 
7925               "                 400       23.06158810662      0.4294426293624\n", 
7926               "             466.667       22.26799054092      0.4106809618644\n", 
7927               "             533.333       21.99851418823      0.4045232104735\n", 
7928               "             666.667       21.19651570955      0.3868136173831\n", 
7929               "             833.333       20.30938498379      0.3682604887899\n", 
7930               "                1000       20.28273252609       0.367719392568\n", 
7931               "# D11\n", 
7932               "              33.333       24.76520269878      0.5026475808706\n", 
7933               "              66.667        24.8773107448      0.5058752916906\n", 
7934               "                 100       24.90357815239      0.5066348551479\n", 
7935               "             133.333        23.7782506151      0.4751950583865\n", 
7936               "             166.667       23.68548762076      0.4727017128631\n", 
7937               "                 200       23.58629651618      0.4700517377679\n", 
7938               "             266.667       23.47734671187      0.4671601744044\n", 
7939               "                 300       24.08647493772      0.4835855560598\n", 
7940               "             333.333       22.98314371029      0.4542918950801\n", 
7941               "                 400       22.80339361568      0.4497107885587\n", 
7942               "             466.667       22.91634335366      0.4525833037874\n", 
7943               "             533.333       22.59774140046      0.4445334311324\n", 
7944               "             666.667        20.9177750759      0.4046955726046\n", 
7945               "             833.333       20.71792550566      0.4002363835007\n", 
7946               "                1000       19.54080006349      0.3751112751853\n", 
7947          ] 
7948   
7949          # Check data_set_600 
7950          file = open(files[0][0]+sep+files[0][1]) 
7951          lines = file.readlines() 
7952          file.close() 
7953          self.assertEqual(len(data_set_600), len(lines)) 
7954          for i in range(len(data_set_600)): 
7955              # Make the string test 
7956              self.assertEqual(data_set_600[i], lines[i]) 
7957   
7958          # Define how files should look like 
7959          data_set_500 = [ 
7960               "50.6846152368\n", 
7961               "0.04\n", 
7962               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
7963               "# G10\n", 
7964               "                  50       22.28084307393      0.2944966344183\n", 
7965               "                 100       21.93494977761      0.2910362768307\n", 
7966               "                 150       21.09850032232       0.282892238351\n", 
7967               "                 200       20.86493960397      0.2806737853646\n", 
7968               "                 250       20.75287269752      0.2796178205016\n", 
7969               "                 300       20.25597152406      0.2750013546989\n", 
7970               "                 350       19.92172163467      0.2719555756504\n", 
7971               "                 400       19.97712052922       0.272457105051\n", 
7972               "                 450       19.46807010415      0.2678972122793\n", 
7973               "                 500       19.76875460947      0.2705774849203\n", 
7974               "                 550       19.39161367402      0.2672216964327\n", 
7975               "                 600       19.03949517697      0.2641417899694\n", 
7976               "                 650       19.12218812132      0.2648605059901\n", 
7977               "                 700       19.01037461457      0.2638893584683\n", 
7978               "                 800       18.83395162904      0.2623674321143\n", 
7979               "                 900       18.47529972436      0.2593123604687\n", 
7980               "                1000        18.5252023121      0.2597343394038\n", 
7981               "# D11\n", 
7982               "                  50       22.15403890237      0.3285588379827\n", 
7983               "                 100       21.80946781746      0.3247185598713\n", 
7984               "                 150       21.77715415505       0.324361526682\n", 
7985               "                 200       21.41647464235      0.3204122024881\n", 
7986               "                 250       21.17099940822      0.3177616325958\n", 
7987               "                 300       21.03740030577      0.3163316496664\n", 
7988               "                 350       20.95393648281      0.3154427665172\n", 
7989               "                 400       20.93311399332       0.315221543436\n", 
7990               "                 450       20.18219905222      0.3073848655291\n", 
7991               "                 500       19.93599065085      0.3048744697057\n", 
7992               "                 550       19.68475725452      0.3023424499113\n", 
7993               "                 600       19.33575433934      0.2988741928798\n", 
7994               "                 650       19.53915692194      0.3008886196853\n", 
7995               "                 700        19.2018754351      0.2975587767134\n", 
7996               "                 800       18.82360965368      0.2938866923878\n", 
7997               "                 900       18.71861761238      0.2928790380131\n", 
7998               "                1000       17.95878049287      0.2857341721151\n", 
7999          ] 
8000   
8001          # Check data_set_500 
8002          file = open(files[1][0]+sep+files[1][1]) 
8003          lines = file.readlines() 
8004          file.close() 
8005          self.assertEqual(len(data_set_500), len(lines)) 
8006          for i in range(len(data_set_500)): 
8007              # Make the string test 
8008              self.assertEqual(data_set_500[i], lines[i]) 
8009   
8010          # Test local dir tests. This will be turned off in system test. 
8011          turn_on_local_dir_test = False 
8012   
8013          if turn_on_local_dir_test: 
8014              ## Now check to local folder with None argument. 
8015              # Write input 
8016              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None) 
8017   
8018              # Check the r2eff set files. 
8019              print("\nChecking the R2eff input set files.") 
8020              files = [[path.join(getcwd(), 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), 'cluster1'), 'sherekhan_frq2.in']] 
8021   
8022              # First check file exists 
8023              for dir, file in files: 
8024                  print(dir+sep+file) 
8025                  self.assert_(access(dir+sep+file, F_OK)) 
8026   
8027              ## Now check to local folder with dir argument. 
8028              # Write input 
8029              set_dir = "Test_ShereKhan" 
8030              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=set_dir) 
8031   
8032              # Check the r2eff set files. 
8033              print("\nChecking the R2eff input set files.") 
8034              files = [[path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq2.in']] 
8035   
8036              # First check file exists 
8037              for dir, file in files: 
8038                  print(dir+sep+file) 
8039                  self.assert_(access(dir+sep+file, F_OK)) 
8040   
8041   
8042 -    def test_sprangers_data_to_mmq_cr72(self, model=None): 
8043          """Test the 'MMQ CR72' model fitting against Remco Sprangers' ClpP data. 
8044   
8045          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MMQ CPMG data with a fixed relaxation time period. 
8046          """ 
8047   
8048          # Reset. 
8049          self.interpreter.reset() 
8050   
8051          # Create the data pipe and load the base data. 
8052          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8053          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8054   
8055          # The model data pipe. 
8056          model = 'MMQ CR72' 
8057          pipe_name = "%s - relax_disp" % model 
8058          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8059          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8060   
8061          # Set the model. 
8062          self.interpreter.relax_disp.select_model(model=model) 
8063   
8064          # Cluster everything. 
8065          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8066   
8067          # Copy the data. 
8068          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8069   
8070          # Alias the spins. 
8071          spin135S = cdp.mol[0].res[0].spin[0] 
8072          spin135F = cdp.mol[0].res[0].spin[1] 
8073          spin137S = cdp.mol[0].res[1].spin[0] 
8074          spin137F = cdp.mol[0].res[1].spin[1] 
8075   
8076          # The R20 keys. 
8077          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
8078          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8079   
8080          # Set the cluster specific parameters (only for the first spin). 
8081          spin135S.pA = 0.836591763632 
8082          spin135S.kex = 241.806525261 
8083   
8084          # Set the initial parameter values. 
8085          spin135S.r2 = {r20_key1: 28.2493431552, r20_key2: 31.7517334715} 
8086          spin135S.dw = 0.583003118785 
8087          spin135S.dwH = 0.0361441944301 
8088   
8089          spin135F.r2 = {r20_key1: 42.7201839991, r20_key2: 57.3178617389} 
8090          spin135F.dw = 0.805849745104 
8091          spin135F.dwH = 0.0215791945715 
8092   
8093          spin137S.r2 = {r20_key1: 26.0134115256, r20_key2: 30.575806934} 
8094          spin137S.dw = 0.688107568372 
8095          spin137S.dwH = 0.0344463604043 
8096   
8097          spin137F.r2 = {r20_key1: 46.6969397337, r20_key2: 58.602384101} 
8098          spin137F.dw = 0.94978299907 
8099          spin137F.dwH = 1.4818877939e-07 
8100   
8101          # Low precision optimisation. 
8102          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-10, max_iter=1000) 
8103   
8104          # Printout. 
8105          print("\n\nOptimised parameters:\n") 
8106          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8107          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8108          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8109          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8110          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8111          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8112          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8113          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8114          print("\n        # Set the cluster specific parameters (only for the first spin).") 
8115          print("        spin135S.pA = %s" % spin135S.pA) 
8116          print("        spin135S.kex = %s" % spin135S.kex) 
8117          print("\n        # Set the initial parameter values.") 
8118          print("        spin135S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135S.r2[r20_key1], spin135S.r2[r20_key2])) 
8119          print("        spin135S.dw = %s" % spin135S.dw) 
8120          print("        spin135S.dwH = %s" % spin135S.dwH) 
8121          print("\n        spin135F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135F.r2[r20_key1], spin135F.r2[r20_key2])) 
8122          print("        spin135F.dw = %s" % spin135F.dw) 
8123          print("        spin135F.dwH = %s" % spin135F.dwH) 
8124          print("\n        spin137S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137S.r2[r20_key1], spin137S.r2[r20_key2])) 
8125          print("        spin137S.dw = %s" % spin137S.dw) 
8126          print("        spin137S.dwH = %s" % spin137S.dwH) 
8127          print("\n        spin137F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137F.r2[r20_key1], spin137F.r2[r20_key2])) 
8128          print("        spin137F.dw = %s" % spin137F.dw) 
8129          print("        spin137F.dwH = %s" % spin137F.dwH) 
8130   
8131          # Checks for residue :135S. 
8132          self.assertAlmostEqual(spin135S.r2[r20_key1], 28.2493445347425, 4) 
8133          self.assertAlmostEqual(spin135S.r2[r20_key2], 31.7517352342937, 4) 
8134          self.assertAlmostEqual(spin135S.pA, 0.836591714049569, 4) 
8135          self.assertAlmostEqual(spin135S.dw, 0.583003004605869, 4) 
8136          self.assertAlmostEqual(spin135S.dwH, 0.0361441894065963, 4) 
8137          self.assertAlmostEqual(spin135S.kex/100, 241.806464344233/100, 4) 
8138          self.assertAlmostEqual(spin135S.chi2, 12.4224060116473, 4) 
8139   
8140          # Checks for residue :135F. 
8141          self.assertAlmostEqual(spin135F.r2[r20_key1], 42.7201844426839, 4) 
8142          self.assertAlmostEqual(spin135F.r2[r20_key2], 57.3178718548898, 4) 
8143          self.assertAlmostEqual(spin135F.pA, 0.836591714049569, 4) 
8144          self.assertAlmostEqual(spin135F.dw, 0.805849748711916, 4) 
8145          self.assertAlmostEqual(spin135F.dwH, 0.0215791669142752, 4) 
8146          self.assertAlmostEqual(spin135F.kex/100, 241.806464344233/100, 4) 
8147          self.assertAlmostEqual(spin135F.chi2, 12.4224060116473, 4) 
8148   
8149          # Checks for residue :137S. 
8150          self.assertAlmostEqual(spin137S.r2[r20_key1], 26.013412509919, 4) 
8151          self.assertAlmostEqual(spin137S.r2[r20_key2], 30.5758092335097, 4) 
8152          self.assertAlmostEqual(spin137S.pA, 0.836591714049569, 4) 
8153          self.assertAlmostEqual(spin137S.dw, 0.688107406812537, 4) 
8154          self.assertAlmostEqual(spin137S.dwH, 0.034446357344577, 4) 
8155          self.assertAlmostEqual(spin137S.kex/100, 241.806464344233/100, 4) 
8156          self.assertAlmostEqual(spin137S.chi2, 12.4224060116473, 4) 
8157   
8158          # Checks for residue :137F. 
8159          self.assertAlmostEqual(spin137F.r2[r20_key1], 46.696935090697, 4) 
8160          self.assertAlmostEqual(spin137F.r2[r20_key2], 58.6023842513446, 4) 
8161          self.assertAlmostEqual(spin137F.pA, 0.836591714049569, 4) 
8162          self.assertAlmostEqual(spin137F.dw, 0.94978325541294, 4) 
8163          self.assertAlmostEqual(spin137F.dwH, 1.5189362257653e-07, 4) 
8164          self.assertAlmostEqual(spin137F.kex/100, 241.806464344233/100, 4) 
8165          self.assertAlmostEqual(spin137F.chi2, 12.4224060116473, 4) 
8166   
8167   
8168 -    def test_sprangers_data_to_ns_mmq_2site(self, model=None): 
8169          """Test the 'NS MMQ 2-site' model fitting against Remco Sprangers' ClpP data. 
8170   
8171          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MQ CPMG data with a fixed relaxation time period. 
8172          """ 
8173   
8174          # Reset. 
8175          self.interpreter.reset() 
8176   
8177          # Create the data pipe and load the base data. 
8178          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8179          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8180   
8181          # The model data pipe. 
8182          model = 'NS MMQ 2-site' 
8183          pipe_name = "%s - relax_disp" % model 
8184          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8185          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8186   
8187          # Set the model. 
8188          self.interpreter.relax_disp.select_model(model=model) 
8189   
8190          # Cluster everything. 
8191          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8192   
8193          # Copy the data. 
8194          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8195   
8196          # Alias the spins. 
8197          spin135S = cdp.mol[0].res[0].spin[0] 
8198          spin135F = cdp.mol[0].res[0].spin[1] 
8199          spin137S = cdp.mol[0].res[1].spin[0] 
8200          spin137F = cdp.mol[0].res[1].spin[1] 
8201   
8202          # The R20 keys. 
8203          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8204          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8205   
8206          # Set the cluster specific parameters (only for the first spin). 
8207          spin135S.pA = 0.847378444499757 
8208          spin135S.kex = 264.055604934724329 
8209   
8210          # Set the initial parameter values. 
8211          spin135S.r2 = {r20_key1: 30.315119723745390, r20_key2: 37.411874745645299} 
8212          spin135S.dw = 0.585574008745351 
8213          spin135S.dwH = 0.000000000000002 
8214   
8215          spin135F.r2 = {r20_key1: 41.440843383778287, r20_key2: 56.989726795397893} 
8216          spin135F.dw = 0.856699277665748 
8217          spin135F.dwH = 0.000000000582587 
8218   
8219          spin137S.r2 = {r20_key1: 23.051695938570266, r20_key2: 28.352806483953824} 
8220          spin137S.dw = 0.772904450844973 
8221          spin137S.dwH = 0.183351478512970 
8222   
8223          spin137F.r2 = {r20_key1: 44.702032074210429, r20_key2: 56.453146052685319} 
8224          spin137F.dw = 0.984568590342831 
8225          spin137F.dwH = 0.000000001993458 
8226   
8227          # Low precision optimisation. 
8228          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-5, grad_tol=None, max_iter=100, constraints=True, scaling=True, verbosity=1) 
8229   
8230          # Printout. 
8231          print("\n\nOptimised parameters:\n") 
8232          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8233          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8234          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8235          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8236          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8237          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8238          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8239          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8240   
8241          # FIXME: Remove this temporary return and properly check the results. 
8242          return 
8243   
8244          # Checks for residue :135S. 
8245          self.assertAlmostEqual(spin135S.r2[r20_key1], 30.3151197237454, 4) 
8246          self.assertAlmostEqual(spin135S.r2[r20_key2], 37.4118747456453, 4) 
8247          self.assertAlmostEqual(spin135S.pA, 0.847378444499757, 4) 
8248          self.assertAlmostEqual(spin135S.dw, 0.585574008745351, 4) 
8249          self.assertAlmostEqual(spin135S.dwH, 2e-15, 4) 
8250          self.assertAlmostEqual(spin135S.kex, 264.055604934724, 4) 
8251          self.assertAlmostEqual(spin135S.chi2, 13.859423588071, 1) 
8252   
8253          # Checks for residue :135F. 
8254          self.assertAlmostEqual(spin135F.r2[r20_key1], 41.4408433837783, 4) 
8255          self.assertAlmostEqual(spin135F.r2[r20_key2], 56.9897267953979, 4) 
8256          self.assertAlmostEqual(spin135F.pA, 0.847378444499757, 4) 
8257          self.assertAlmostEqual(spin135F.dw, 0.856699277665748, 4) 
8258          self.assertAlmostEqual(spin135F.dwH, 5.82587e-10, 4) 
8259          self.assertAlmostEqual(spin135F.kex, 264.055604934724, 4) 
8260          self.assertAlmostEqual(spin135F.chi2, 13.859423588071, 1) 
8261   
8262          # Checks for residue :137S. 
8263          self.assertAlmostEqual(spin137S.r2[r20_key1], 23.0516959385703, 4) 
8264          self.assertAlmostEqual(spin137S.r2[r20_key2], 28.3528064839538, 4) 
8265          self.assertAlmostEqual(spin137S.pA, 0.847378444499757, 4) 
8266          self.assertAlmostEqual(spin137S.dw, 0.772904450844973, 4) 
8267          self.assertAlmostEqual(spin137S.dwH, 0.18335147851297, 4) 
8268          self.assertAlmostEqual(spin137S.kex, 264.055604934724, 4) 
8269          self.assertAlmostEqual(spin137S.chi2, 13.859423588071, 1) 
8270   
8271          # Checks for residue :137F. 
8272          self.assertAlmostEqual(spin137F.r2[r20_key1], 44.7020320742104, 4) 
8273          self.assertAlmostEqual(spin137F.r2[r20_key2], 56.4531460526853, 4) 
8274          self.assertAlmostEqual(spin137F.pA, 0.847378444499757, 4) 
8275          self.assertAlmostEqual(spin137F.dw, 0.984568590342831, 4) 
8276          self.assertAlmostEqual(spin137F.dwH, 2.0931309e-09, 4) 
8277          self.assertAlmostEqual(spin137F.kex, 264.055604934724, 4) 
8278          self.assertAlmostEqual(spin137F.chi2, 13.859423588071, 1) 
8279   
8280   
8281 -    def test_tp02_data_to_ns_r1rho_2site(self, model=None): 
8282          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
8283   
8284          # Setup the data. 
8285          self.setup_tp02_data_to_ns_r1rho_2site() 
8286   
8287          # Alias the spins. 
8288          spin1 = cdp.mol[0].res[0].spin[0] 
8289          spin2 = cdp.mol[0].res[1].spin[0] 
8290   
8291          # The R20 keys. 
8292          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8293          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8294   
8295          # Checks for residue :1. 
8296          self.assertAlmostEqual(spin1.r2[r20_key1], 8.50207717367548, 4) 
8297          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4680429589972, 4) 
8298          self.assertAlmostEqual(spin1.pA, 0.864523128842393, 4) 
8299          self.assertAlmostEqual(spin1.dw, 8.85204828994151, 4) 
8300          self.assertAlmostEqual(spin1.kex/1000, 1199.56359549637/1000, 4) 
8301          self.assertAlmostEqual(spin1.chi2, 2.99182130153514, 4) 
8302   
8303          # Checks for residue :2. 
8304          self.assertAlmostEqual(spin2.r2[r20_key1], 10.2099357790203, 4) 
8305          self.assertAlmostEqual(spin2.r2[r20_key2], 16.2137648697873, 4) 
8306          self.assertAlmostEqual(spin2.pA, 0.836488681031685, 4) 
8307          self.assertAlmostEqual(spin2.dw, 9.5505714779503, 4) 
8308          self.assertAlmostEqual(spin2.kex/1000, 1454.45726998929/1000, 4) 
8309          self.assertAlmostEqual(spin2.chi2, 0.000402231563481261, 4) 
8310   
8311   
8312 -    def test_tp02_data_to_ns_r1rho_2site_cluster(self, model=None): 
8313          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data, when performing clustering.""" 
8314   
8315          # Setup the data. 
8316          self.setup_tp02_data_to_ns_r1rho_2site(clustering=True) 
8317   
8318          # Alias the spins. 
8319          spin1 = cdp.mol[0].res[0].spin[0] 
8320          spin2 = cdp.mol[0].res[1].spin[0] 
8321   
8322          # The R20 keys. 
8323          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8324          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8325   
8326          # Checks for residue :1. 
8327          self.assertAlmostEqual(spin1.r2[r20_key1], 8.48607207881462, 4) 
8328          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4527609061722, 4) 
8329          self.assertAlmostEqual(spin1.pA, 0.863093838784425, 4) 
8330          self.assertAlmostEqual(spin1.dw, 8.86218096536618, 4) 
8331          self.assertAlmostEqual(spin1.kex/1000, 1186.22749648299/1000, 4) 
8332          self.assertAlmostEqual(spin1.chi2, 3.09500996065247, 4) 
8333   
8334          # Checks for residue :2. 
8335          self.assertAlmostEqual(spin2.r2[r20_key1], 10.4577906018883, 4) 
8336          self.assertAlmostEqual(spin2.r2[r20_key2], 16.4455550953792, 4) 
8337          self.assertAlmostEqual(spin2.pA, 0.863093838784425, 4) 
8338          self.assertAlmostEqual(spin2.dw, 11.5841168862587, 4) 
8339          self.assertAlmostEqual(spin2.kex/1000, 1186.22749648299/1000, 4) 
8340          self.assertAlmostEqual(spin2.chi2, 3.09500996065247, 4) 
8341   
8342   
8343 -    def test_tp02_data_to_mp05(self): 
8344          """Test the dispersion 'MP05' model fitting against the 'TP02' test data.""" 
8345   
8346          # Fixed time variable and the models. 
8347          ds.fixed = True 
8348          ds.models = ['R2eff', 'MP05'] 
8349   
8350          # Execute the script. 
8351          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8352   
8353          # Switch back to the data pipe for the optimisation. 
8354          self.interpreter.pipe.switch('MP05 - relax_disp') 
8355   
8356          # The equivalent MP05 parameters. 
8357          r1rho_prime = [[10.0058086343329, 15.005806870124], [12.0766320470785, 18.0767503536277]] 
8358          pA = [0.775055484521586, 0.500000000036595] 
8359          kex = [1235.20361276079, 2378.31403454691] 
8360          delta_omega = [7.08194146569694, 5.4083562844306] 
8361          chi2 = [0.0370400968727768, 0.182141732163934] 
8362   
8363          # Alias the spins. 
8364          spin1 = cdp.mol[0].res[0].spin[0] 
8365          spin2 = cdp.mol[0].res[1].spin[0] 
8366   
8367          # The R20 keys. 
8368          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8369          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8370   
8371          # Printout. 
8372          print("\n\nOptimised parameters:\n") 
8373          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8374          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8375          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8376          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8377          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8378          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8379          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8380   
8381          # Check each spin. 
8382          spin_index = 0 
8383          for spin, spin_id in spin_loop(return_id=True): 
8384              # Printout. 
8385              print("\nSpin %s." % spin_id) 
8386   
8387              # Check the fitted parameters. 
8388              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8389              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8390              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8391              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8392              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8393              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8394   
8395              # Increment the spin index. 
8396              spin_index += 1 
8397   
8398   
8399 -    def test_tp02_data_to_tap03(self): 
8400          """Test the dispersion 'TAP03' model fitting against the 'TP02' test data.""" 
8401   
8402          # Fixed time variable and the models. 
8403          ds.fixed = True 
8404          ds.models = ['R2eff', 'TAP03'] 
8405   
8406          # Execute the script. 
8407          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8408   
8409          # Switch back to the data pipe for the optimisation. 
8410          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8411   
8412          # The equivalent TAP03 parameters. 
8413          r1rho_prime = [[10.0058156589442, 15.005818505006], [12.0766046472748, 18.076648462452]] 
8414          pA = [0.775042569092891, 0.500000000229685] 
8415          kex = [1235.20852748765, 2379.47085580169] 
8416          delta_omega = [7.08176806468445, 5.40708372863538] 
8417          chi2 = [0.0371366837083293, 0.182212857256044] 
8418   
8419          # Alias the spins. 
8420          spin1 = cdp.mol[0].res[0].spin[0] 
8421          spin2 = cdp.mol[0].res[1].spin[0] 
8422   
8423          # The R20 keys. 
8424          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8425          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8426   
8427          # Printout. 
8428          print("\n\nOptimised parameters:\n") 
8429          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8430          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8431          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8432          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8433          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8434          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8435          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8436   
8437          # Switch to the 'MP05' model data pipe, then check for each spin. 
8438          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8439          spin_index = 0 
8440          for spin, spin_id in spin_loop(return_id=True): 
8441              # Printout. 
8442              print("\nSpin %s." % spin_id) 
8443   
8444              # Check the fitted parameters. 
8445              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8446              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8447              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8448              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8449              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8450              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8451   
8452              # Increment the spin index. 
8453              spin_index += 1 
8454   
8455   
8456 -    def test_tp02_data_to_tp02(self): 
8457          """Test the relaxation dispersion 'TP02' model curve fitting to fixed time synthetic data.""" 
8458   
8459          # Fixed time variable. 
8460          ds.fixed = True 
8461   
8462          # Execute the script. 
8463          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8464   
8465          # The original parameters. 
8466          r1rho_prime = [[10.0, 15.0], [12.0, 18.0]] 
8467          pA = 0.7654321 
8468          kex = 1234.56789 
8469          delta_omega = [7.0, 9.0] 
8470   
8471          # The R20 keys. 
8472          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8473          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8474   
8475          # Switch to the 'TP02' model data pipe, then check for each spin. 
8476          self.interpreter.pipe.switch('TP02 - relax_disp') 
8477          spin_index = 0 
8478          for spin, spin_id in spin_loop(return_id=True): 
8479              # Printout. 
8480              print("\nSpin %s." % spin_id) 
8481   
8482              # Check the fitted parameters. 
8483              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8484              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8485              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8486              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 3) 
8487   
8488              # Increment the spin index. 
8489              spin_index += 1 
8490   
8491   
8492 -    def test_value_write_calc_rotating_frame_params_int(self): 
8493          """System test of the value.write function to write intensities for an R1rho setup. 
8494          This system test is to make sure, that modifying the API for special parameters theta and w_eff does not alter the functionality value.write. 
8495   
8496          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8497          """ 
8498   
8499          # Load the state. 
8500          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8501          self.interpreter.state.load(statefile, force=True) 
8502   
8503          # Set filepaths. 
8504          int_filepath = ds.tmpdir+sep+'int.out' 
8505   
8506          # Write out the intensity parameter file. 
8507          # The writing out of intensity file is to make sure the API function retains its function after modification for special parameters. 
8508          self.interpreter.value.write(param='peak_intensity', file='int.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8509   
8510          # Test the file exists. 
8511          self.assert_(access(int_filepath, F_OK)) 
8512   
8513          # Open the files for testing. 
8514          int_file = open(int_filepath, 'r') 
8515   
8516          # Loop over the intensity file to test values. 
8517          for line in int_file: 
8518              # Skip lines starting with #. 
8519              if line[0] == "#": 
8520                  continue 
8521   
8522              # Split the line 
8523              linesplit = line.split() 
8524   
8525              # Assume values 
8526              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8527                  self.assertEqual(linesplit[5], "115571.4") 
8528              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8529                  self.assertEqual(linesplit[5], "68377.52") 
8530              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8531                  self.assertEqual(linesplit[5], "9141.689") 
8532              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8533                  self.assertEqual(linesplit[5], "29123.77") 
8534              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8535                  self.assertEqual(linesplit[5], "58914.94") 
8536   
8537          # Close files 
8538          int_file.close() 
8539   
8540   
8541 -    def test_value_write_calc_rotating_frame_params_theta(self): 
8542          """System test of the value.write function to write return values of theta from calc_rotating_frame_params() function for an R1rho setup. 
8543   
8544          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8545          """ 
8546   
8547          # Load the state. 
8548          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8549          self.interpreter.state.load(statefile, force=True) 
8550   
8551          # Set filepaths. 
8552          theta_filepath = ds.tmpdir+sep+'theta.out' 
8553   
8554          # Write out the theta parameter file. 
8555          self.interpreter.value.write(param='theta', file='theta.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8556   
8557          # Test the file exists. 
8558          self.assert_(access(theta_filepath, F_OK)) 
8559   
8560          # Open the files for testing. 
8561          theta_file = open(theta_filepath, 'r') 
8562   
8563          # Loop over the theta file to test values. 
8564          for line in theta_file: 
8565              # Skip lines starting with #. 
8566              if line[0] == "#": 
8567                  continue 
8568              # Print lines, not including newline character. 
8569              print(line[:-1]) 
8570   
8571              # Split the line 
8572              linesplit = line.split() 
8573   
8574              # Assume values 
8575              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8576                  self.assertNotEqual(linesplit[5], "None") 
8577              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8578                  self.assertNotEqual(linesplit[5], "None") 
8579              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8580                  self.assertNotEqual(linesplit[5], "None") 
8581              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8582                  self.assertNotEqual(linesplit[5], "None") 
8583              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8584                  self.assertNotEqual(linesplit[5], "None") 
8585   
8586          # Close files 
8587          theta_file.close() 
8588   
8589   
8590 -    def test_value_write_calc_rotating_frame_params_w_eff(self): 
8591          """System test of the value.write function to write return values of w_eff from calc_rotating_frame_params() function for an R1rho setup. 
8592   
8593          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8594          """ 
8595   
8596          # Load the state. 
8597          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8598          self.interpreter.state.load(statefile, force=True) 
8599   
8600          # Set filepaths. 
8601          w_eff_filepath = ds.tmpdir+sep+'w_eff.out' 
8602   
8603          # Write out the w_eff parameter file. 
8604          self.interpreter.value.write(param='w_eff', file='w_eff.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8605   
8606          # Test the file exists. 
8607          self.assert_(access(w_eff_filepath, F_OK)) 
8608   
8609          # Open the files for testing. 
8610          w_eff_file = open(w_eff_filepath, 'r') 
8611   
8612          # Loop over the w_eff file to test values. 
8613          for line in w_eff_file: 
8614              # Skip lines starting with #. 
8615              if line[0] == "#": 
8616                  continue 
8617              # Print lines, not including newline character. 
8618              print(line[:-1]) 
8619   
8620              # Split the line 
8621              linesplit = line.split() 
8622   
8623              # Assume values 
8624              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8625                  self.assertNotEqual(linesplit[5], "None") 
8626              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8627                  self.assertNotEqual(linesplit[5], "None") 
8628              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8629                  self.assertNotEqual(linesplit[5], "None") 
8630              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8631                  self.assertNotEqual(linesplit[5], "None") 
8632              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8633                  self.assertNotEqual(linesplit[5], "None") 
8634   
8635          # Close files 
8636          w_eff_file.close() 
8637   
8638   
8639 -    def test_value_write_calc_rotating_frame_params_auto_analysis(self): 
8640          """System test of the auto_analysis value.write function to write theta and w_eff values for an R1rho setup. 
8641   
8642          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8643          """ 
8644   
8645          # Load the state. 
8646          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344.bz2' 
8647          self.interpreter.state.load(statefile, force=True) 
8648   
8649          # Set pipe name, bundle and type. 
8650          pipe_name = 'base pipe' 
8651          pipe_bundle = 'relax_disp' 
8652          pipe_type = 'relax_disp' 
8653   
8654          # The path to the data files. 
8655          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
8656   
8657          # Deselect all spins 
8658          self.interpreter.deselect.all() 
8659   
8660          # Specify spins to be selected. 
8661          select_spin_ids = [ 
8662          ":13@N", 
8663          ":15@N", 
8664          ":16@N", 
8665          ":25@N", 
8666          ":26@N", 
8667          ":28@N", 
8668          ":39@N", 
8669          ":40@N", 
8670          ":41@N", 
8671          ":43@N", 
8672          ":44@N", 
8673          ":45@N", 
8674          ":49@N", 
8675          ":52@N", 
8676          ":53@N"] 
8677   
8678          # Reverse the selection for the spins. 
8679          for curspin in select_spin_ids: 
8680              print("Selecting spin %s"%curspin) 
8681              self.interpreter.deselect.reverse(spin_id=curspin) 
8682   
8683          # Read the R1 data 
8684          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
8685   
8686          # The dispersion models. 
8687          MODELS = ['R2eff'] 
8688   
8689          # The grid search size (the number of increments per dimension). 
8690          GRID_INC = 4 
8691   
8692          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
8693          MC_NUM = 3 
8694   
8695          # Model selection technique. 
8696          MODSEL = 'AIC' 
8697   
8698          # Execute the auto-analysis (fast). 
8699          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
8700          OPT_FUNC_TOL = 1e-1 
8701          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
8702          OPT_MAX_ITERATIONS = 1000 
8703          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
8704   
8705          # Run the analysis. 
8706          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
8707   
8708          ## Check for file creation 
8709          # Set filepaths. 
8710          theta_filepath = ds.tmpdir+sep+MODELS[0]+sep+'theta.out' 
8711          w_eff_filepath = ds.tmpdir+sep+MODELS[0]+sep+'w_eff.out' 
8712   
8713          # Test the files exists. 
8714          self.assert_(access(theta_filepath, F_OK)) 
8715          self.assert_(access(w_eff_filepath, F_OK)) 
8716   
8717          # Open the files for testing. 
8718          theta_file = open(theta_filepath, 'r') 
8719          theta_result = [ 
8720              "# Parameter description:  Rotating frame tilt angle : ( theta = arctan(w_1 / Omega) ) (rad).\n", 
8721              "#\n", 
8722              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
8723              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8724              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8725              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8726              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8727              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8728              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8729              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8730              "None          13         L           None        N                1.83827367612531                   None                                           1.79015307643158                   None                                            2.2768687598681                  None                                          2.08461171779445                  None                                          2.00120623474388                  None                                          1.92825070277699                  None                                          1.47212860033516                   None                                           1.12978017906854                   None                                           1.20415336139956                   None                                          0.901691390796334                  None                                         0.687390207543568                   None                                          0.455635480573046                  None                                         0.281637123971289                   None                                          0.138259661766539                   None                                       \n", 
8731              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8732              "None          15         R           None        N                1.58367544790673                   None                                           1.58127411936947                   None                                           1.61085209029811                  None                                          1.59731540507347                  None                                          1.59237108385522                  None                                          1.58834866344307                  None                                           1.2251048782537                   None                                          0.938142786712004                   None                                           1.03297495592991                   None                                          0.683284686224254                  None                                         0.594447788256641                   None                                          0.383528609383686                  None                                         0.262780814059893                   None                                          0.133469839450564                   None                                       \n", 
8733              "None          16         T           None        N                1.40984232256624                   None                                           1.43947245672073                   None                                           1.10299856647417                  None                                          1.24811470332083                  None                                          1.30521602599932                  None                                          1.35302443831853                  None                                          1.07923777467974                   None                                          0.833345927788896                   None                                          0.934350308974616                   None                                          0.581325254389991                  None                                         0.543659670184793                   None                                          0.346238480454282                  None                                         0.251454336191817                   None                                          0.130436714663781                   None                                       \n", 
8734              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8735              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8736              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8737              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8738              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8739              "None          25         Q           None        N                1.81569700258844                   None                                           1.77137827615015                   None                                           2.23175875585624                  None                                          2.04612705363098                  None                                           1.9673155780155                  None                                          1.89908711012298                  None                                          1.44829660124856                   None                                           1.11023386429581                   None                                           1.18716091371256                   None                                          0.877306975624962                  None                                         0.677790118853413                   None                                          0.447932002242236                  None                                         0.279785379050945                   None                                          0.137802891887767                   None                                       \n", 
8740              "None          26         Q           None        N                1.61128821168674                   None                                           1.60374392042003                   None                                           1.69619923953765                  None                                          1.65403989292986                  None                                          1.63856717205868                  None                                          1.62595755714564                  None                                          1.24977859227795                   None                                          0.956353494917591                   None                                           1.04972090035774                   None                                          0.702164059520172                  None                                         0.603227813742091                   None                                          0.390116910781037                  None                                         0.264658552037535                   None                                          0.133960994297096                   None                                       \n", 
8741              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8742              "None          28         Q           None        N                1.65182797011356                   None                                           1.63676707684161                   None                                           1.81830827892972                  None                                           1.7365089711986                  None                                          1.70601955220877                  None                                          1.68102938663686                  None                                          1.28685736157369                   None                                          0.984047498595701                   None                                            1.0749792109454                   None                                          0.731585685663053                  None                                         0.616577997665602                   None                                          0.400219205533665                  None                                         0.267471993812649                   None                                          0.134690869499646                   None                                       \n", 
8743              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8744              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8745              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8746              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8747              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8748              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8749              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8750              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8751              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8752              "None          39         L           None        N                1.76426439181176                   None                                           1.72885318885161                   None                                           2.11826300085737                  None                                          1.95430201082222                  None                                          1.88794717058464                  None                                          1.83172922971397                  None                                          1.39549951193417                   None                                           1.06783946148624                   None                                           1.14997013232702                   None                                          0.826128785942585                  None                                         0.657105386950171                   None                                          0.431542911580536                  None                                         0.275725736430539                   None                                          0.136791385554619                   None                                       \n", 
8753              "None          40         M           None        N                 1.5521741199158                   None                                           1.55564594516135                   None                                           1.51290906497298                  None                                          1.53245929150759                  None                                          1.53960430408466                  None                                          1.54541832596591                  None                                          1.19750223001929                   None                                          0.917959090226757                   None                                           1.01428385962747                   None                                          0.662779584695967                  None                                         0.584708929219264                   None                                          0.376271266885303                  None                                         0.260671619214194                   None                                          0.132914250767089                   None                                       \n", 
8754              "None          41         A           None        N                1.68339451828261                   None                                           1.66252964414082                   None                                           1.90911961276946                  None                                          1.79959323497326                  None                                          1.75801925517113                  None                                          1.72370710837265                  None                                          1.31646868936419                   None                                           1.00647189763597                   None                                           1.09525348649914                   None                                           0.75605702767542                  None                                         0.627395557358039                   None                                          0.408481831044309                  None                                         0.269716174238842                   None                                          0.135267948387412                   None                                       \n", 
8755              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8756              "None          43         F           None        N                1.58506597154432                   None                                           1.58240542750303                   None                                           1.61517196062351                  None                                          1.60017740004898                  None                                          1.59469990835425                  None                                          1.59024353162528                  None                                          1.22633651794829                   None                                          0.939047922181951                   None                                           1.03380990731605                   None                                          0.684214484755514                  None                                         0.594884298549546                   None                                          0.383855128702894                  None                                         0.262874695048502                   None                                           0.13349447283116                   None                                       \n", 
8757              "None          44         I           None        N                1.57575471961837                   None                                           1.57483015671791                   None                                           1.58622388390755                  None                                          1.58100758841935                  None                                          1.57910319967536                  None                                          1.57755415552211                  None                                          1.21811077066835                   None                                          0.933010299763027                   None                                           1.02823520295828                   None                                           0.67802911457195                  None                                         0.591972285081647                   None                                          0.381678892926696                  None                                         0.262247347241724                   None                                          0.133329708422379                   None                                       \n", 
8758              "None          45         K           None        N                1.77147501495754                   None                                           1.73479633022489                   None                                           2.13509660780385                  None                                          1.96751045408372                  None                                          1.89924480319914                  None                                          1.84124387452692                  None                                          1.40277881643715                   None                                           1.07361367582571                   None                                           1.15506365550891                   None                                          0.832963505534767                  None                                         0.659913187081268                   None                                          0.433751178249555                  None                                         0.276282572106685                   None                                           0.13693095791902                   None                                       \n", 
8759              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8760              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8761              "None          49         A           None        N                2.00297059962685                   None                                           1.92978318052058                   None                                           2.53305709323468                  None                                          2.33052197276846                  None                                          2.22870514722639                  None                                          2.13201782446864                  None                                           1.6587904412969                   None                                           1.29333162369472                   None                                           1.34311052758116                   None                                           1.12559033900783                  None                                         0.770195063841652                   None                                          0.524846264860003                  None                                         0.296857751274362                   None                                          0.141908833673671                   None                                       \n", 
8762              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8763              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8764              "None          52         V           None        N                1.82421571143794                   None                                           1.77845404105203                   None                                           2.24910726268822                  None                                          2.06078232916932                  None                                          1.98017451806059                  None                                          1.91012195713554                  None                                          1.45724107606646                   None                                           1.11753869321304                   None                                           1.19352234944057                   None                                          0.886361068343012                  None                                         0.681372607920812                   None                                          0.450799407357501                  None                                         0.280478735779163                   None                                          0.137974257665877                   None                                       \n", 
8765              "None          53         A           None        N                2.05019708195234                   None                                           1.97089957318506                   None                                           2.58789168363698                  None                                          2.39027806684801                  None                                          2.28731354878582                  None                                           2.1872118539319                  None                                           1.7165709935896                   None                                           1.34832362477229                   None                                           1.38879751095815                   None                                            1.2085314357749                  None                                         0.799450059125864                   None                                          0.550583841461621                  None                                          0.30195492609136                   None                                          0.143090604877102                   None                                       \n", 
8766              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8767              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8768              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8769              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8770              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
8771          ] 
8772          # Check the created theta file. 
8773          lines = theta_file.readlines() 
8774          for i in range(len(lines)): 
8775              # Test lines starting with # 
8776              if theta_result[i][0] == "#": 
8777                  self.assertEqual(theta_result[i], lines[i]) 
8778              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
8779              if theta_result[i] == lines[i]: 
8780                  self.assertEqual(theta_result[i], lines[i]) 
8781              # If the line is not equal each other, make a slower comparison of values. 
8782              else: 
8783                  # Print lines if they don't match. To help find differences. 
8784                  print(theta_result[i]) 
8785                  print(lines[i]) 
8786   
8787                  # First test first 62 characters containing spin information 
8788                  self.assertEqual(theta_result[i][:62], lines[i][:62]) 
8789   
8790                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
8791                  theta_result_s = theta_result[i][62:].split()[::2] 
8792                  print(theta_result_s ) 
8793                  lines_s = lines[i][62:].split()[::2] 
8794                  print(lines_s) 
8795                  # Loop over the value elements 
8796                  for j in range(len(lines_s)): 
8797                      print(theta_result_s[j], lines_s[j]) 
8798                      # Assume a precision to digits. 
8799                      self.assertAlmostEqual(float(theta_result_s[j]), float(lines_s[j]), 14) 
8800   
8801          # Close file 
8802          theta_file.close() 
8803   
8804          w_eff_file = open(w_eff_filepath, 'r') 
8805          w_eff_result = [ 
8806              "# Parameter description:  Effective field in rotating frame : ( w_eff = sqrt(Omega^2 + w_1^2) ) (rad.s^-1).\n", 
8807              "#\n", 
8808              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
8809              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8810              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8811              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8812              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8813              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8814              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8815              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8816              "None          13         L           None        N                8737.12883908829                   None                                           10612.1226552258                   None                                           3558.93734069587                  None                                          4698.27194621826                  None                                          5534.46153956037                  None                                          6599.82570817753                  None                                          8467.62674839481                   None                                           9318.00441649087                   None                                           11095.2662520767                   None                                           6412.33580591254                  None                                          13279.9803044242                   None                                            11430.254637056                  None                                          30318.7268264644                   None                                           61141.1080046448                   None                                       \n", 
8817              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8818              "None          15         R           None        N                8427.14155005377                   None                                           10358.3995676635                   None                                           2710.22680763322                  None                                          4093.04942975722                  None                                          5030.86065069262                  None                                          6183.60685459024                  None                                          8956.28403254202                   None                                           10448.6627754369                   None                                           12060.4428066937                   None                                           7966.64282975241                  None                                          15045.8392092364                   None                                           13441.3586252373                  None                                          32438.4764809909                   None                                           63321.5201471181                   None                                       \n", 
8819              "None          16         T           None        N                 8536.7818857229                   None                                            10447.792678989                   None                                           3034.01707453628                  None                                           4314.2767521567                  None                                          5212.43600885913                  None                                          6332.21319855067                  None                                          9558.14311447582                   None                                           11384.2336494604                   None                                           12879.4604966293                   None                                           9159.34604475399                  None                                          16290.1746838959                   None                                           14821.0200530829                  None                                          33866.5933527757                   None                                           64785.3205696403                   None                                       \n", 
8820              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8821              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8822              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8823              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8824              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8825              "None          25         Q           None        N                8685.60895531182                   None                                           10569.7459677762                   None                                           3430.51272680396                  None                                          4601.75421490393                  None                                          5452.76508815826                  None                                          6531.46859076009                  None                                          8490.06475886501                   None                                           9406.58372902508                   None                                           11169.7602637607                   None                                           6540.38696356753                  None                                          13437.7348017798                   None                                           11613.1632549021                  None                                          30514.0741594726                   None                                           61342.4792156782                   None                                       \n", 
8826              "None          26         Q           None        N                8433.35533683544                   None                                           10363.4554631194                   None                                           2729.48656005151                  None                                          4105.82770792005                  None                                          5041.26238350827                  None                                          6192.07245313098                  None                                          8880.08366342131                   None                                           10312.6868786802                   None                                           11942.8320576165                   None                                           7787.44854491812                  None                                          14853.4987024375                   None                                           13225.7048162038                  None                                          32213.6690023282                   None                                           63090.7407990801                   None                                       \n", 
8827              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8828              "None          28         Q           None        N                8454.18308422202                   None                                           10380.4112885894                   None                                           2793.17494362899                  None                                          4148.43953208179                  None                                          5076.02756135055                  None                                          6220.40920270029                  None                                          8777.91538040813                   None                                           10118.8737706315                   None                                           11775.8792998529                   None                                           7528.90766101027                  None                                          14572.4015102398                   None                                            12909.211050939                  None                                          31882.8171856889                   None                                           62750.9120842199                   None                                       \n", 
8829              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8830              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8831              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8832              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8833              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8834              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8835              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8836              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8837              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8838              "None          39         L           None        N                 8586.6405431352                   None                                           10488.5710521378                   None                                           3171.59430904777                  None                                          4412.11227722123                  None                                          5293.69814015286                  None                                          6399.27143075725                  None                                          8557.58926327909                   None                                           9617.45773774313                   None                                           11347.9169998729                   None                                           6840.20010813426                  None                                          13795.1250622375                   None                                           12024.9041436853                  None                                           30951.651485352                   None                                           61793.2130509111                   None                                       \n", 
8839              "None          40         M           None        N                8427.90394711227                   None                                           10359.0198301036                   None                                           2712.59646573568                  None                                          4094.61889210019                  None                                          5032.13762965554                  None                                           6184.6458240746                  None                                          9049.68452800053                   None                                           10607.7913029633                   None                                           12198.5639821231                   None                                           8174.23271685285                  None                                          15266.4924700447                   None                                           13687.9010998756                  None                                          32694.9043143038                   None                                           63584.6371927381                   None                                       \n", 
8840              "None          41         A           None        N                8480.14299737436                   None                                           10401.5648897003                   None                                           2870.79081440785                  None                                          4201.09083283266                  None                                          5119.14733505123                  None                                          6255.64579267482                  None                                          8706.50768957471                   None                                           9972.71017314947                   None                                           11650.5225246067                   None                                           7331.28858930568                  None                                          14354.1616183112                   None                                           12662.3378547029                  None                                          31623.9195264738                   None                                           62484.8290612112                   None                                       \n", 
8841              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8842              "None          43         F           None        N                8427.30062786474                   None                                           10358.5289868368                   None                                            2710.7214015056                  None                                          4093.37694357637                  None                                          5031.12711571215                  None                                          6183.82364721878                  None                                          8952.31975962078                   None                                           10441.7375680915                   None                                           12054.4435931163                   None                                           7957.55789315654                  None                                          15036.1316712316                   None                                           13430.4914212645                  None                                          32427.1596037519                   None                                           63309.9050677925                   None                                       \n", 
8843              "None          44         I           None        N                8426.54623319716                   None                                           10357.9152496503                   None                                            2708.3751705368                  None                                          4091.82359712664                  None                                          5029.86337809029                  None                                          6182.79552045043                  None                                          8979.12144335458                   None                                           10488.2688526334                   None                                           12094.7720286018                   None                                           8018.51779989075                  None                                          15101.1843990883                   None                                           13503.2816173444                  None                                          32502.9389163062                   None                                           63387.6763306952                   None                                       \n", 
8844              "None          45         K           None        N                8599.01176345321                   None                                           10498.7013581079                   None                                           3204.93649737055                  None                                          4436.14046641897                  None                                          5313.74138343704                  None                                          6415.86177652694                  None                                          8546.79665373249                   None                                           9587.16245449134                   None                                           11322.2529042385                   None                                           6797.53838612575                  None                                          13745.1536613763                   None                                           11967.5433300612                  None                                          30890.8603419261                   None                                           61730.6213936947                   None                                       \n", 
8845              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8846              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8847              "None          49         A           None        N                9279.63849130869                   None                                           11063.0654625247                   None                                           4737.11992391463                  None                                          5643.40583860235                  None                                          6356.45614406507                  None                                          7302.87406141381                  None                                          8459.17105047661                   None                                           8761.54554569995                   None                                           10632.2343488142                   None                                           5572.92782399155                  None                                          12102.1714908775                   None                                           10037.6988885228                  None                                          28806.6916858172                   None                                           59579.0348769179                   None                                       \n", 
8848              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8849              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8850              "None          52         V           None        N                8704.45610117774                   None                                           10585.2389163429                   None                                            3477.9549539207                  None                                          4637.22923167743                  None                                          5482.73656118686                  None                                           6556.5108895527                  None                                          8481.06470969555                   None                                           9372.86414918436                   None                                           11141.3782476763                   None                                           6491.79686536093                  None                                          13378.2843939736                   None                                           11544.3205736882                  None                                            30440.62308788                   None                                           61266.7742546508                   None                                       \n", 
8851              "None          53         A           None        N                9497.02860450276                   None                                           11246.0339326126                   None                                           5149.96766581255                  None                                          5994.15475647208                  None                                          6669.81232845336                  None                                          7577.19152075731                  None                                          8516.77431951689                   None                                           8639.36099840319                   None                                           10531.7750336522                   None                                           5378.79193153767                  None                                          11752.8060152439                   None                                           9613.59939949642                  None                                          28334.9153747994                   None                                           59090.2988815445                   None                                       \n", 
8852              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8853              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8854              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8855              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8856              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
8857          ] 
8858          # Check the created w_eff file. 
8859          lines = w_eff_file.readlines() 
8860          for i in range(len(lines)): 
8861              # Test lines starting with # 
8862              if w_eff_result[i][0] == "#": 
8863                  self.assertEqual(w_eff_result[i], lines[i]) 
8864              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
8865              if w_eff_result[i] == lines[i]: 
8866                  self.assertEqual(w_eff_result[i], lines[i]) 
8867              # If the line is not equal each other, make a slower comparison of values. 
8868              else: 
8869                  # Print lines if they don't match. To help find differences. 
8870                  print(w_eff_result[i]) 
8871                  print(lines[i]) 
8872   
8873                  # First test first 62 characters containing spin information 
8874                  self.assertEqual(w_eff_result[i][:62], lines[i][:62]) 
8875   
8876                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
8877                  w_eff_result_s = w_eff_result[i][62:].split()[::2] 
8878                  print(w_eff_result_s ) 
8879                  lines_s = lines[i][62:].split()[::2] 
8880                  print(lines_s) 
8881                  # Loop over the value elements 
8882                  for j in range(len(lines_s)): 
8883                      print(w_eff_result_s[j], lines_s[j]) 
8884                      # Assume a precision to digits. 
8885                      self.assertAlmostEqual(float(w_eff_result_s[j]), float(lines_s[j]), 14) 
8886   
8887          # Close file 
8888          w_eff_file.close() 
8889   
8890   
8891 -    def verify_estimate_r2eff_err_compare_mc(self): 
8892          """Test the user function for estimating R2eff errors from exponential curve fitting, and compare it with Monte-Carlo simulations. 
8893   
8894          This follows Task 7822. 
8895          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
8896   
8897          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
8898          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
8899          """ 
8900   
8901          # Load the data. 
8902          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
8903   
8904          # Set pipe name, bundle and type. 
8905          pipe_name = 'base pipe' 
8906          pipe_bundle = 'relax_disp' 
8907          pipe_type = 'relax_disp' 
8908   
8909          # Create the data pipe. 
8910          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
8911   
8912          file = data_path + '1_setup_r1rho_GUI.py' 
8913          self.interpreter.script(file=file, dir=None) 
8914   
8915          # Deselect all spins. 
8916          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
8917   
8918          # Select one spin. 
8919          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
8920   
8921          # Set the model. 
8922          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
8923   
8924          # Check if intensity errors have already been calculated. 
8925          check_intensity_errors() 
8926   
8927          # Do a grid search. 
8928          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
8929   
8930          # Set algorithm. 
8931          min_algor = 'Newton' 
8932          constraints = True 
8933          if constraints: 
8934              min_options = ('%s'%(min_algor),) 
8935              #min_algor = 'Log barrier' 
8936              min_algor = 'Method of Multipliers' 
8937              scaling_matrix = assemble_scaling_matrix(scaling=True) 
8938   
8939              # Collect spins 
8940              all_spin_ids = [] 
8941              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8942                  all_spin_ids.append(spin_id) 
8943   
8944              spins = spin_ids_to_containers(all_spin_ids[:1]) 
8945   
8946              # Get constraints 
8947              A, b = linear_constraints(spins=spins, scaling_matrix=scaling_matrix[0]) 
8948          else: 
8949              min_options = () 
8950              A, b = None, None 
8951          min_options = () 
8952          sim_boot = 200 
8953          scaling_list = [1.0, 1.0] 
8954   
8955          # Minimise. 
8956          self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints, verbosity=1) 
8957   
8958          # Loop over old err attributes. 
8959          err_attr_list = ['r2eff_err', 'i0_err'] 
8960   
8961          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8962              # Loop over old err attributes. 
8963              for err_attr in err_attr_list: 
8964                  if hasattr(cur_spin, err_attr): 
8965                      delattr(cur_spin, err_attr) 
8966   
8967          # Collect the estimation data from boot. 
8968          my_dic = {} 
8969          param_key_list = [] 
8970          est_keys = [] 
8971          est_key = '-2' 
8972          est_keys.append(est_key) 
8973          spin_id_list = [] 
8974   
8975          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8976              # Add key to dic. 
8977              my_dic[spin_id] = {} 
8978   
8979              # Add key for estimate. 
8980              my_dic[spin_id][est_key] = {} 
8981   
8982              # Add spin key to list. 
8983              spin_id_list.append(spin_id) 
8984   
8985              # Generate spin string. 
8986              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
8987   
8988              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
8989                  # Generate the param_key. 
8990                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
8991   
8992                  # Append key. 
8993                  param_key_list.append(param_key) 
8994   
8995                  # Add key to dic. 
8996                  my_dic[spin_id][est_key][param_key] = {} 
8997   
8998                  values = [] 
8999                  errors = [] 
9000                  times = [] 
9001                  for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
9002                      values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
9003                      errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
9004                      times.append(time) 
9005   
9006                  # Convert to numpy array. 
9007                  values = asarray(values) 
9008                  errors = asarray(errors) 
9009                  times = asarray(times) 
9010   
9011                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
9012                  i0 = getattr(cur_spin, 'i0')[param_key] 
9013   
9014                  R_m_sim_l = [] 
9015                  I0_m_sim_l = [] 
9016                  for j in range(sim_boot): 
9017                      if j in range(0, 100000, 100): 
9018                          print("Simulation %i"%j) 
9019                      # Start minimisation. 
9020   
9021                      # Produce errors 
9022                      I_err = [] 
9023                      for j, error in enumerate(errors): 
9024                          I_error = gauss(values[j], error) 
9025                          I_err.append(I_error) 
9026                      # Convert to numpy array. 
9027                      I_err = asarray(I_err) 
9028   
9029                      x0 = [r2eff, i0] 
9030                      model = Relax_fit_opt(num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
9031   
9032                      # Ref input. 
9033                      #def generic_minimise(func=None, dfunc=None, d2func=None, args=(), x0=None, min_algor=None, min_options=None, func_tol=1e-25, grad_tol=None, maxiter=1e6, A=None, b=None, l=None, u=None, c=None, dc=None, d2c=None, print_flag=0, print_prefix="", full_output=False): 
9034                      # l=l, u=u, c=c, dc=dc, d2c=d2c 
9035                      # l: Lower bound constraint vector (l <= x <= u). 
9036                      # u: Upper bound constraint vector (l <= x <= u). 
9037                      # c: User supplied constraint function. 
9038                      # dc: User supplied constraint gradient function. 
9039                      params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, A=A, b=b, full_output=True, print_flag=0) 
9040   
9041                      R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
9042                      R_m_sim_l.append(R_m_sim_j) 
9043                      I0_m_sim_l.append(I0_m_sim_j) 
9044   
9045                  # Get stats on distribution. 
9046                  sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
9047                  sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
9048                  my_dic[spin_id][est_key][param_key]['r2eff_err'] = sigma_R_sim 
9049                  my_dic[spin_id][est_key][param_key]['i0_err'] = sigma_I0_sim 
9050   
9051          # Estimate R2eff errors. 
9052          self.interpreter.relax_disp.r2eff_err_estimate() 
9053   
9054          est_key = '-1' 
9055          est_keys.append(est_key) 
9056   
9057          # Collect data. 
9058          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9059              # Add key for estimate. 
9060              my_dic[spin_id][est_key] = {} 
9061   
9062              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9063                  # Generate the param_key. 
9064                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9065   
9066                  # Add key to dic. 
9067                  my_dic[spin_id][est_key][param_key] = {} 
9068   
9069                  # Get the value. 
9070                  # Loop over err attributes. 
9071                  for err_attr in err_attr_list: 
9072                      if hasattr(cur_spin, err_attr): 
9073                          get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9074                      else: 
9075                          get_err_attr = 0.0 
9076   
9077                      # Save to dic. 
9078                      my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9079   
9080   
9081          # Make Carlo Simulations number 
9082          mc_number_list = list(range(0, 1000, 250)) 
9083   
9084          sim_attr_list = ['chi2_sim', 'f_count_sim', 'g_count_sim', 'h_count_sim', 'i0_sim', 'iter_sim', 'peak_intensity_sim', 'r2eff_sim', 'select_sim', 'warning_sim'] 
9085   
9086          # Loop over the Monte Carlo simulations: 
9087          for number in mc_number_list: 
9088              # First delete old simulations. 
9089              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9090                  # Loop over old err attributes. 
9091                  for err_attr in err_attr_list: 
9092                      if hasattr(cur_spin, err_attr): 
9093                          delattr(cur_spin, err_attr) 
9094   
9095                  # Loop over the simulated attributes. 
9096                  for sim_attr in sim_attr_list: 
9097                      if hasattr(cur_spin, sim_attr): 
9098                          delattr(cur_spin, sim_attr) 
9099   
9100              self.interpreter.monte_carlo.setup(number=number) 
9101              self.interpreter.monte_carlo.create_data() 
9102              self.interpreter.monte_carlo.initial_values() 
9103              self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints) 
9104              self.interpreter.eliminate() 
9105              self.interpreter.monte_carlo.error_analysis() 
9106   
9107              est_key = '%i'%number 
9108              est_keys.append(est_key) 
9109   
9110              # Collect data. 
9111              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9112                  # Add key for estimate. 
9113                  my_dic[spin_id][est_key] = {} 
9114   
9115                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9116                      # Generate the param_key. 
9117                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9118   
9119                      # Add key to dic. 
9120                      my_dic[spin_id][est_key][param_key] = {} 
9121   
9122                      # Get the value. 
9123                      # Loop over err attributes. 
9124                      for err_attr in err_attr_list: 
9125                          if hasattr(cur_spin, err_attr): 
9126                              get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9127                          else: 
9128                              get_err_attr = 0.0 
9129   
9130                          # Save to dic. 
9131                          my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9132   
9133          # Set what to extract. 
9134          err_attr = err_attr_list[0] 
9135   
9136          # Define list with text. 
9137          text_list = [] 
9138   
9139          # Now loop through the data. 
9140          for spin_id in spin_id_list: 
9141              for est_key in est_keys: 
9142                  # Define list to pickup data. 
9143                  r2eff_err_list = [] 
9144   
9145                  for param_key in param_key_list: 
9146                      # Get the value. 
9147                      r2eff_err = my_dic[spin_id][est_key][param_key][err_attr] 
9148   
9149                      # Add to list. 
9150                      r2eff_err_list.append(r2eff_err) 
9151   
9152                  # Sum the list 
9153                  sum_array = sum(array(r2eff_err_list)) 
9154   
9155                  # Join floats to string. 
9156                  r2eff_err_str = " ".join(format(x, "2.3f") for x in r2eff_err_list) 
9157   
9158                  # Define print string. 
9159                  text = "%8s %s sum= %2.3f" % (est_key, r2eff_err_str, sum_array) 
9160                  text_list.append(text) 
9161   
9162   
9163          # Now print. 
9164          filepath = NamedTemporaryFile(delete=False).name 
9165          # Open the files for testing. 
9166          w_file = open(filepath, 'w') 
9167   
9168          print("Printing the estimated R2eff error as function of estimation from Co-variance and number of Monte-Carlo simulations.") 
9169   
9170          for text in text_list: 
9171              # Print. 
9172              print(text) 
9173   
9174              # Write to file. 
9175              w_file.write(text+"\n") 
9176   
9177          # Close files 
9178          w_file.close() 
9179   
9180          print("Filepath is: %s"%filepath) 
9181          print("Start 'gnuplot' and write:") 
9182          print("set term dumb") 
9183          print("plot '%s' using 1:17 title 'R2eff error as function of MC number' w linespoints "%filepath) 
9184   
9185   
9186 -    def verify_r1rho_kjaergaard_missing_r1(self, models=None, result_dir_name=None, r2eff_estimate=None): 
9187          """Verification of test_r1rho_kjaergaard_missing_r1.""" 
9188   
9189          # Check the kex value of residue 52 
9190          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
9191   
9192          # Print results for each model. 
9193          print("\n\n################") 
9194          print("Printing results") 
9195          print("################\n") 
9196          for model in models: 
9197              # Skip R2eff model. 
9198              if model == MODEL_R2EFF: 
9199                  continue 
9200   
9201              # Switch to pipe. 
9202              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9203              print("\nModel: %s" % (model)) 
9204   
9205              # Loop over the spins. 
9206              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9207                  # Generate spin string. 
9208                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9209   
9210                  # Loop over the parameters. 
9211                  print("Optimised parameters for spin: %s" % (spin_string)) 
9212                  for param in cur_spin.params + ['chi2']: 
9213                      # Get the value. 
9214                      if param in ['r1', 'r2']: 
9215                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
9216                              # Generate the R20 key. 
9217                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
9218   
9219                              # Get the value. 
9220                              value = getattr(cur_spin, param)[r20_key] 
9221   
9222                              # Print value. 
9223                              print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9224   
9225                              # Compare values. 
9226                              if spin_id == ':52@N': 
9227                                  if param == 'r1': 
9228                                      if model == MODEL_NOREX: 
9229                                          if r2eff_estimate == 'direct': 
9230                                              self.assertAlmostEqual(value, 1.46138805) 
9231                                          elif r2eff_estimate == 'MC2000': 
9232                                              self.assertAlmostEqual(value, 1.46328102) 
9233                                          elif r2eff_estimate == 'chi2_pyt': 
9234                                              self.assertAlmostEqual(value, 1.43820629) 
9235                                      elif model == MODEL_DPL94: 
9236                                          if r2eff_estimate == 'direct': 
9237                                              self.assertAlmostEqual(value, 1.44845742) 
9238                                          elif r2eff_estimate == 'MC2000': 
9239                                              self.assertAlmostEqual(value, 1.45019848) 
9240                                          elif r2eff_estimate == 'chi2_pyt': 
9241                                              self.assertAlmostEqual(value, 1.44666512) 
9242                                      elif model == MODEL_TP02: 
9243                                          if r2eff_estimate == 'direct': 
9244                                              self.assertAlmostEqual(value, 1.54354392) 
9245                                          elif r2eff_estimate == 'MC2000': 
9246                                              self.assertAlmostEqual(value, 1.54352369) 
9247                                          elif r2eff_estimate == 'chi2_pyt': 
9248                                              self.assertAlmostEqual(value, 1.55964020) 
9249                                      elif model == MODEL_TAP03: 
9250                                          if r2eff_estimate == 'direct': 
9251                                              self.assertAlmostEqual(value, 1.54356410) 
9252                                          elif r2eff_estimate == 'MC2000': 
9253                                              self.assertAlmostEqual(value, 1.54354367) 
9254                                          elif r2eff_estimate == 'chi2_pyt': 
9255                                              self.assertAlmostEqual(value, 1.55967157) 
9256                                      elif model == MODEL_MP05: 
9257                                          if r2eff_estimate == 'direct': 
9258                                              self.assertAlmostEqual(value, 1.54356416) 
9259                                          elif r2eff_estimate == 'MC2000': 
9260                                              self.assertAlmostEqual(value, 1.54354372) 
9261                                          elif r2eff_estimate == 'chi2_pyt': 
9262                                              self.assertAlmostEqual(value, 1.55967163) 
9263                                      elif model == MODEL_NS_R1RHO_2SITE: 
9264                                          if r2eff_estimate == 'direct': 
9265                                              self.assertAlmostEqual(value, 1.41359221, 5) 
9266                                          elif r2eff_estimate == 'MC2000': 
9267                                              self.assertAlmostEqual(value, 1.41321968, 5) 
9268                                          elif r2eff_estimate == 'chi2_pyt': 
9269                                              self.assertAlmostEqual(value, 1.36303129, 5) 
9270   
9271                                  elif param == 'r2': 
9272                                      if model == MODEL_NOREX: 
9273                                          if r2eff_estimate == 'direct': 
9274                                              self.assertAlmostEqual(value, 11.48392439) 
9275                                          elif r2eff_estimate == 'MC2000': 
9276                                              self.assertAlmostEqual(value, 11.48040934) 
9277                                          elif r2eff_estimate == 'chi2_pyt': 
9278                                              self.assertAlmostEqual(value, 11.47224488) 
9279                                      elif model == MODEL_DPL94: 
9280                                          if r2eff_estimate == 'direct': 
9281                                              self.assertAlmostEqual(value, 10.15688372, 6) 
9282                                          elif r2eff_estimate == 'MC2000': 
9283                                              self.assertAlmostEqual(value, 10.16304887, 6) 
9284                                          elif r2eff_estimate == 'chi2_pyt': 
9285                                              self.assertAlmostEqual(value, 9.20037797, 6) 
9286                                      elif model == MODEL_TP02: 
9287                                          if r2eff_estimate == 'direct': 
9288                                              self.assertAlmostEqual(value, 9.72654896, 6) 
9289                                          elif r2eff_estimate == 'MC2000': 
9290                                              self.assertAlmostEqual(value, 9.72772726, 6) 
9291                                          elif r2eff_estimate == 'chi2_pyt': 
9292                                              self.assertAlmostEqual(value, 9.53948340, 6) 
9293                                      elif model == MODEL_TAP03: 
9294                                          if r2eff_estimate == 'direct': 
9295                                              self.assertAlmostEqual(value, 9.72641887, 6) 
9296                                          elif r2eff_estimate == 'MC2000': 
9297                                              self.assertAlmostEqual(value, 9.72759374, 6) 
9298                                          elif r2eff_estimate == 'chi2_pyt': 
9299                                              self.assertAlmostEqual(value, 9.53926913, 6) 
9300                                      elif model == MODEL_MP05: 
9301                                          if r2eff_estimate == 'direct': 
9302                                              self.assertAlmostEqual(value, 9.72641723, 6) 
9303                                          elif r2eff_estimate == 'MC2000': 
9304                                              self.assertAlmostEqual(value, 9.72759220, 6) 
9305                                          elif r2eff_estimate == 'chi2_pyt': 
9306                                              self.assertAlmostEqual(value, 9.53926778, 6) 
9307                                      elif model == MODEL_NS_R1RHO_2SITE: 
9308                                          if r2eff_estimate == 'direct': 
9309                                              self.assertAlmostEqual(value, 9.34531535, 5) 
9310                                          elif r2eff_estimate == 'MC2000': 
9311                                              self.assertAlmostEqual(value, 9.34602793, 5) 
9312                                          elif r2eff_estimate == 'chi2_pyt': 
9313                                              self.assertAlmostEqual(value, 9.17631409, 5) 
9314   
9315                      # For all other parameters. 
9316                      else: 
9317                          # Get the value. 
9318                          value = getattr(cur_spin, param) 
9319   
9320                          # Print value. 
9321                          print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9322   
9323                          # Compare values. 
9324                          if spin_id == ':52@N': 
9325                              if param == 'phi_ex': 
9326                                  if model == MODEL_DPL94: 
9327                                      if r2eff_estimate == 'direct': 
9328                                          self.assertAlmostEqual(value, 0.07599563) 
9329                                      elif r2eff_estimate == 'MC2000': 
9330                                          self.assertAlmostEqual(value, 0.07561937) 
9331                                      elif r2eff_estimate == 'chi2_pyt': 
9332                                          self.assertAlmostEqual(value, 0.12946061) 
9333   
9334                              elif param == 'pA': 
9335                                  if model == MODEL_TP02: 
9336                                      if r2eff_estimate == 'direct': 
9337                                          self.assertAlmostEqual(value, 0.88827040) 
9338                                      elif r2eff_estimate == 'MC2000': 
9339                                          self.assertAlmostEqual(value, 0.88807487) 
9340                                      elif r2eff_estimate == 'chi2_pyt': 
9341                                          self.assertAlmostEqual(value, 0.87746233) 
9342                                  elif model == MODEL_TAP03: 
9343                                      if r2eff_estimate == 'direct': 
9344                                          self.assertAlmostEqual(value, 0.88828922) 
9345                                      elif r2eff_estimate == 'MC2000': 
9346                                          self.assertAlmostEqual(value, 0.88809318) 
9347                                      elif r2eff_estimate == 'chi2_pyt': 
9348                                          self.assertAlmostEqual(value, 0.87747558) 
9349                                  elif model == MODEL_MP05: 
9350                                      if r2eff_estimate == 'direct': 
9351                                          self.assertAlmostEqual(value, 0.88828924, 6) 
9352                                      elif r2eff_estimate == 'MC2000': 
9353                                          self.assertAlmostEqual(value, 0.88809321) 
9354                                      elif r2eff_estimate == 'chi2_pyt': 
9355                                          self.assertAlmostEqual(value, 0.87747562) 
9356                                  elif model == MODEL_NS_R1RHO_2SITE: 
9357                                      if r2eff_estimate == 'direct': 
9358                                          self.assertAlmostEqual(value, 0.94504369, 6) 
9359                                      elif r2eff_estimate == 'MC2000': 
9360                                          self.assertAlmostEqual(value, 0.94496541, 6) 
9361                                      elif r2eff_estimate == 'chi2_pyt': 
9362                                          self.assertAlmostEqual(value, 0.92084707, 6) 
9363   
9364                              elif param == 'dw': 
9365                                  if model == MODEL_TP02: 
9366                                      if r2eff_estimate == 'direct': 
9367                                          self.assertAlmostEqual(value, 1.08875840, 6) 
9368                                      elif r2eff_estimate == 'MC2000': 
9369                                          self.assertAlmostEqual(value, 1.08765638, 6) 
9370                                      elif r2eff_estimate == 'chi2_pyt': 
9371                                          self.assertAlmostEqual(value, 1.09753230, 6) 
9372                                  elif model == MODEL_TAP03: 
9373                                      if r2eff_estimate == 'direct': 
9374                                          self.assertAlmostEqual(value, 1.08837238, 6) 
9375                                      elif r2eff_estimate == 'MC2000': 
9376                                          self.assertAlmostEqual(value, 1.08726698, 6) 
9377                                      elif r2eff_estimate == 'chi2_pyt': 
9378                                          self.assertAlmostEqual(value, 1.09708821, 6) 
9379                                  elif model == MODEL_MP05: 
9380                                      if r2eff_estimate == 'direct': 
9381                                          self.assertAlmostEqual(value, 1.08837241, 6) 
9382                                      elif r2eff_estimate == 'MC2000': 
9383                                          self.assertAlmostEqual(value, 1.08726706, 6) 
9384                                      elif r2eff_estimate == 'chi2_pyt': 
9385                                          self.assertAlmostEqual(value, 1.09708832, 6) 
9386                                  elif model == MODEL_NS_R1RHO_2SITE: 
9387                                      if r2eff_estimate == 'direct': 
9388                                          self.assertAlmostEqual(value, 1.56001812, 5) 
9389                                      elif r2eff_estimate == 'MC2000': 
9390                                          self.assertAlmostEqual(value, 1.55833321, 5) 
9391                                      elif r2eff_estimate == 'chi2_pyt': 
9392                                          self.assertAlmostEqual(value, 1.36406712, 5) 
9393   
9394                              elif param == 'kex': 
9395                                  if model == MODEL_DPL94: 
9396                                      if r2eff_estimate == 'direct': 
9397                                          self.assertAlmostEqual(value/1e5, 4460.43711569/1e5, 7) 
9398                                      elif r2eff_estimate == 'MC2000': 
9399                                          self.assertAlmostEqual(value/1e5, 4419.03917195/1e5, 7) 
9400                                      elif r2eff_estimate == 'chi2_pyt': 
9401                                          self.assertAlmostEqual(value/1e5, 6790.22736344/1e5, 7) 
9402                                  elif model == MODEL_TP02: 
9403                                      if r2eff_estimate == 'direct': 
9404                                          self.assertAlmostEqual(value/1e5, 4921.28602757/1e5, 7) 
9405                                      elif r2eff_estimate == 'MC2000': 
9406                                          self.assertAlmostEqual(value/1e5, 4904.70144883/1e5, 7) 
9407                                      elif r2eff_estimate == 'chi2_pyt': 
9408                                          self.assertAlmostEqual(value/1e5, 5146.20306591/1e5, 7) 
9409                                  elif model == MODEL_TAP03: 
9410                                      if r2eff_estimate == 'direct': 
9411                                          self.assertAlmostEqual(value/1e5, 4926.42963491/1e5, 7) 
9412                                      elif r2eff_estimate == 'MC2000': 
9413                                          self.assertAlmostEqual(value/1e5, 4909.86877150/1e5, 7) 
9414                                      elif r2eff_estimate == 'chi2_pyt': 
9415                                          self.assertAlmostEqual(value/1e5, 5152.51105814/1e5, 7) 
9416                                  elif model == MODEL_MP05: 
9417                                      if r2eff_estimate == 'direct': 
9418                                          self.assertAlmostEqual(value/1e5, 4926.44236315/1e5, 7) 
9419                                      elif r2eff_estimate == 'MC2000': 
9420                                          self.assertAlmostEqual(value/1e5, 4909.88110195/1e5, 7) 
9421                                      elif r2eff_estimate == 'chi2_pyt': 
9422                                          self.assertAlmostEqual(value/1e5, 5152.52097111/1e5, 7) 
9423                                  elif model == MODEL_NS_R1RHO_2SITE: 
9424                                      if r2eff_estimate == 'direct': 
9425                                          self.assertAlmostEqual(value/1e5, 5628.66061488/1e5, 6) 
9426                                      elif r2eff_estimate == 'MC2000': 
9427                                          self.assertAlmostEqual(value/1e5, 5610.20221435/1e5, 6) 
9428                                      elif r2eff_estimate == 'chi2_pyt': 
9429                                          self.assertAlmostEqual(value/1e5, 5643.34067090/1e5, 6) 
9430   
9431                              elif param == 'chi2': 
9432                                  if model == MODEL_NOREX: 
9433                                      if r2eff_estimate == 'direct': 
9434                                          self.assertAlmostEqual(value, 848.42016907, 5) 
9435                                      elif r2eff_estimate == 'MC2000': 
9436                                          self.assertAlmostEqual(value, 3363.95829122, 5) 
9437                                      elif r2eff_estimate == 'chi2_pyt': 
9438                                          self.assertAlmostEqual(value, 5976.49946726, 5) 
9439                                  elif model == MODEL_DPL94: 
9440                                      if r2eff_estimate == 'direct': 
9441                                          self.assertAlmostEqual(value, 179.47041241) 
9442                                      elif r2eff_estimate == 'MC2000': 
9443                                          self.assertAlmostEqual(value, 710.24767560) 
9444                                      elif r2eff_estimate == 'chi2_pyt': 
9445                                          self.assertAlmostEqual(value, 612.72616697, 5) 
9446                                  elif model == MODEL_TP02: 
9447                                      if r2eff_estimate == 'direct': 
9448                                          self.assertAlmostEqual(value, 29.33882530, 6) 
9449                                      elif r2eff_estimate == 'MC2000': 
9450                                          self.assertAlmostEqual(value, 114.47142772, 6) 
9451                                      elif r2eff_estimate == 'chi2_pyt': 
9452                                          self.assertAlmostEqual(value, 250.50838162, 5) 
9453                                  elif model == MODEL_TAP03: 
9454                                      if r2eff_estimate == 'direct': 
9455                                          self.assertAlmostEqual(value, 29.29050673, 6) 
9456                                      elif r2eff_estimate == 'MC2000': 
9457                                          self.assertAlmostEqual(value, 114.27987534) 
9458                                      elif r2eff_estimate == 'chi2_pyt': 
9459                                          self.assertAlmostEqual(value, 250.04050719, 5) 
9460                                  elif model == MODEL_MP05: 
9461                                      if r2eff_estimate == 'direct': 
9462                                          self.assertAlmostEqual(value, 29.29054301, 6) 
9463                                      elif r2eff_estimate == 'MC2000': 
9464                                          self.assertAlmostEqual(value, 114.28002272) 
9465                                      elif r2eff_estimate == 'chi2_pyt': 
9466                                          self.assertAlmostEqual(value, 250.04077478, 5) 
9467                                  elif model == MODEL_NS_R1RHO_2SITE: 
9468                                      if r2eff_estimate == 'direct': 
9469                                          self.assertAlmostEqual(value, 34.44010543, 6) 
9470                                      elif r2eff_estimate == 'MC2000': 
9471                                          self.assertAlmostEqual(value, 134.14368365) 
9472                                      elif r2eff_estimate == 'chi2_pyt': 
9473                                          self.assertAlmostEqual(value, 278.55121388, 5) 
9474   
9475   
9476          # Print the final pipe. 
9477          model = 'final' 
9478          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9479          print("\nFinal pipe") 
9480   
9481          # Loop over the spins. 
9482          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9483              # Generate spin string. 
9484              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9485   
9486              # Loop over the parameters. 
9487              print("Optimised model for spin: %s" % (spin_string)) 
9488              param = 'model' 
9489   
9490              # Get the value. 
9491              value = getattr(cur_spin, param) 
9492              print("%-10s %-6s %-6s %6s" % ("Parameter:", param, "Value:", value)) 
9493   
9494   
9495          ### Now check some of the written out files. 
9496          file_names = ['r1rho_prime', 'r1'] 
9497   
9498          for file_name_i in file_names: 
9499   
9500              # Make the file name. 
9501              file_name = "%s.out" % file_name_i 
9502   
9503              # Get the file path. 
9504              file_path = get_file_path(file_name, result_dir_name + sep + model) 
9505   
9506              # Test the file exists. 
9507              print("Testing file access to: %s"%file_path) 
9508              self.assert_(access(file_path, F_OK)) 
9509   
9510              # Now open, and compare content, line by line. 
9511              file_prod = open(file_path) 
9512              lines_prod = file_prod.readlines() 
9513              file_prod.close() 
9514   
9515              # Loop over the lines. 
9516              for i, line in enumerate(lines_prod): 
9517                  # Make the string test 
9518                  line_split = line.split() 
9519   
9520                  # Continue for comment lines. 
9521                  if line_split[0] == "#": 
9522                      print(line), 
9523                      continue 
9524   
9525                  # Assign the split of the line. 
9526                  mol_name, res_num, res_name, spin_num, spin_name, val, sd_error = line_split 
9527                  print(mol_name, res_num, res_name, spin_num, spin_name, val, sd_error) 
9528   
9529                  if res_num == '52': 
9530                      # Assert that the value is not None. 
9531                      self.assertNotEqual(val, 'None') 
9532